Paper Digest: CVPR 2013 Highlights

July 24, 2013October 6, 2019 admin

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) is one of the top computer vision conferences in the world. In 2013, it is to be held in Portland, Oregon.

To help AI community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.

We thank all authors for writing these interesting papers, and readers for reading our digests. If you do not want to miss any interesting AI paper, you are welcome to sign up our free paper digest service to get new paper updates customized to your own interests on a daily basis.

Paper Digest Team
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TABLE 1: CVPR 2013 Papers

	Title	Authors	Highlight
1	Deformable Spatial Pyramid Matching for Fast Dense Correspondences	Jaechul Kim, Ce Liu, Fei Sha, Kristen Grauman	Whereas the prevailing approaches operate at the pixel level, we propose a pyramid graph model that simultaneously regularizes match consistency at multiple spatial extents–ranging from an entire image, to coarse grid cells, to every single pixel.
2	A Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles	Dror Sholomon, Omid David, Nathan S. Netanyahu	In this paper we propose the first effective automated, genetic algorithm (GA)-based jigsaw puzzle solver.
3	Exploring Compositional High Order Pattern Potentials for Structured Output Learning	Yujia Li, Daniel Tarlow, Richard Zemel	In this work, we study the learning of a general class of pattern-like high order potential, which we call Compositional High Order Pattern Potentials (CHOPPs).
4	Hyperbolic Harmonic Mapping for Constrained Brain Surface Registration	Rui Shi, Wei Zeng, Zhengyu Su, Hanna Damasio, Zhonglin Lu, Yalin Wang, Shing-Tung Yau, Xianfeng Gu	We apply our algorithm to study constrained human brain surface registration problem.
5	Dense Variational Reconstruction of Non-rigid Surfaces from Monocular Video	Ravi Garg, Anastasios Roussos, Lourdes Agapito	This paper offers the first variational approach to the problem of dense 3D reconstruction of non-rigid surfaces from a monocular video sequence.
6	Fusing Depth from Defocus and Stereo with Coded Apertures	Yuichi Takeda, Shinsaku Hiura, Kosuke Sato	In this paper we propose a novel depth measurement method by fusing depth from defocus (DFD) and stereo.
7	A Non-parametric Framework for Document Bleed-through Removal	Roisin Rowley-Brooke, Francois Pitie, Anil Kokaram	This paper presents recent work on a new framework for non-blind document bleed-through removal.
8	A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems	J. Kappes, B. Andres, F. Hamprecht, C. Schnorr, S. Nowozin, D. Batra, S. Kim, B. Kausler, J. Lellmann, N. Komodakis, C. Rother	Key insights from our study agree with the results of Szeliski et al. for the types of models they studied.
9	Submodular Salient Region Detection	Zhuolin Jiang, Larry S. Davis	The similarities are efficiently computed by finding a closed-form harmonic solution on the constructed graph for an input image.
10	Spatio-temporal Depth Cuboid Similarity Feature for Activity Recognition Using Depth Camera	Lu Xia, J.K. Aggarwal	In this paper, we propose its counterpart in depth video and show its efficacy on activity recognition.
11	Bringing Semantics into Focus Using Visual Abstraction	C. L. Zitnick, Devi Parikh	In this paper, we propose studying semantic information in abstract images created from collections of clip art. We create 1,002 sets of 10 semantically similar abstract scenes with corresponding written descriptions.
12	Fast Multiple-Part Based Object Detection Using KD-Ferns	Dan Levi, Shai Silberstein, Aharon Bar-Hillel	In this work we present a new part-based object detection algorithm with hundreds of parts performing realtime detection.
13	Computing Diffeomorphic Paths for Large Motion Interpolation	Dohyung Seo, Jeffrey Ho, Baba C. Vemuri	In this paper, we introduce a novel framework for computing a path of diffeomorphisms between a pair of input diffeomorphisms.
14	Wide-Baseline Hair Capture Using Strand-Based Refinement	Linjie Luo, Cha Zhang, Zhengyou Zhang, Szymon Rusinkiewicz	We propose a novel algorithm to reconstruct the 3D geometry of human hairs in wide-baseline setups using strand-based refinement.
15	Radial Distortion Self-Calibration	Jose Henrique Brito, Roland Angst, Kevin Koser, Marc Pollefeys	By finding these straight epipolar lines in camera pairs we can obtain constraints on the distortion center(s) without any calibration object or plumbline assumptions in the scene.
16	Separating Signal from Noise Using Patch Recurrence across Scales	Maria Zontak, Inbar Mosseri, Michal Irani	In this paper we show how this multi-scale property can be extended to solve ill-posed problems under noisy conditions, such as image denoising.
17	Detection Evolution with Multi-order Contextual Co-occurrence	Guang Chen, Yuanyuan Ding, Jing Xiao, Tony X. Han	In this paper we propose an effective representation, Multi-Order Contextual co-Occurrence (MOCO), to implicitly model the high level context using solely detection responses from a baseline object detector.
18	Manhattan Scene Understanding via XSlit Imaging	Jinwei Ye, Yu Ji, Jingyi Yu	In this paper, we present a novel single-image MW reconstruction algorithm from the perspective of nonpinhole cameras.
19	Cumulative Attribute Space for Age and Crowd Density Estimation	Ke Chen, Shaogang Gong, Tao Xiang, Chen Change Loy	Encouraged by the recent success in using attributes for solving classification problems with sparse training data, this paper introduces a novel cumulative attribute concept for learning a regression model when only sparse and imbalanced data are available.
20	Tensor-Based High-Order Semantic Relation Transfer for Semantic Scene Segmentation	Heesoo Myeong, Kyoung Mu Lee	We propose a novel nonparametric approach for semantic segmentation using high-order semantic relations.
21	Accurate and Robust Registration of Nonrigid Surface Using Hierarchical Statistical Shape Model	Hidekata Hontani, Yuto Tsunekawa, Yoshihide Sawada	In this paper, we propose a new non-rigid robust registration method that registers a point distribution model (PDM) of a surface to given 3D images.
22	Sparse Quantization for Patch Description	Xavier Boix, Michael Gygli, Gemma Roig, Luc Van Gool	We present a novel formulation of patch description, that serves such issues well.
23	What’s in a Name? First Names as Facial Attributes	Huizhong Chen, Andrew C. Gallagher, Bernd Girod	This paper introduces a new idea in describing people using their first names, i.e., the name assigned at birth.
24	Context-Aware Modeling and Recognition of Activities in Video	Yingying Zhu, Nandita M. Nayak, Amit K. Roy-Chowdhury	In this paper, rather than modeling activities in videos individually, we propose a hierarchical framework that jointly models and recognizes related activities using motion and various context features.
25	Learning to Detect Partially Overlapping Instances	Carlos Arteta, Victor Lempitsky, J. A. Noble, Andrew Zisserman	The objective of this work is to detect all instances of a class (such as cells or people) in an image.
26	Exemplar-Based Face Parsing	Brandon M. Smith, Li Zhang, Jonathan Brandt, Zhe Lin, Jianchao Yang	In this work, we propose an exemplar-based face image segmentation algorithm.
27	Multipath Sparse Coding Using Hierarchical Matching Pursuit	Liefeng Bo, Xiaofeng Ren, Dieter Fox	We propose Multipath Hierarchical Matching Pursuit (M-HMP), a novel feature learning architecture that combines a collection of hierarchical sparse features for image classification to capture multiple aspects of discriminative structures.
28	Visual Tracking via Locality Sensitive Histograms	Shengfeng He, Qingxiong Yang, Rynson W.H. Lau, Jiang Wang, Ming-Hsuan Yang	This paper presents a novel locality sensitive histogram algorithm for visual tracking.
29	Optimized Product Quantization for Approximate Nearest Neighbor Search	Tiezheng Ge, Kaiming He, Qifa Ke, Jian Sun	In this paper, we optimize product quantization by minimizing quantization distortions w.r.t. the space decomposition and the quantization codebooks.
30	Tracking People and Their Objects	Tobias Baumgartner, Dennis Mitzel, Bastian Leibe	In this paper, we propose a probabilistic approach for classifying such person-object interactions, associating objects to persons, and predicting how the interaction will most likely continue.
31	Multi-target Tracking by Lagrangian Relaxation to Min-cost Network Flow	Asad A. Butt, Robert T. Collins	We propose a method for global multi-target tracking that can incorporate higher-order track smoothness constraints such as constant velocity.
32	In Defense of 3D-Label Stereo	Carl Olsson, Johannes Ulen, Yuri Boykov	In this paper we advocate a largely overlooked alternative approach to stereo where 2nd order surface smoothness is represented by pairwise interactions with 3D-labels, e.g. tangent planes.
33	Compressible Motion Fields	Giuseppe Ottaviano, Pushmeet Kohli	In this paper, we address the problem of estimating dense motion fields that, while accurately predicting one frame from a given reference frame by warping it with the field, are also compressible.
34	Dense Object Reconstruction with Semantic Priors	Sid Yingze Bao, Manmohan Chandraker, Yuanqing Lin, Silvio Savarese	We present a dense reconstruction approach that overcomes the drawbacks of traditional multiview stereo by incorporating semantic information in the form of learned category-level shape priors and object detection.
35	Large-Scale Video Summarization Using Web-Image Priors	Aditya Khosla, Raffay Hamid, Chih-Jen Lin, Neel Sundaresan	In this work, we apply our novel insight to develop a summarization algorithm that uses the web-image based prior information in an unsupervised manner.
36	Deformable Graph Matching	Feng Zhou, Fernando De la Torre	The key idea of this work is a new factorization of the pair-wise affinity matrix.
37	3D Visual Proxemics: Recognizing Human Interactions in 3D from a Single Image	Ishani Chakraborty, Hui Cheng, Omar Javed	We present a unified framework for detecting and classifying people interactions in unconstrained user generated images.
38	Dictionary Learning from Ambiguously Labeled Data	Yi-Chen Chen, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa, P. J. Phillips	We propose a novel dictionary-based learning method for ambiguously labeled multiclass classification, where each training sample has multiple labels and only one of them is the correct label.
39	Graph-Based Optimization with Tubularity Markov Tree for 3D Vessel Segmentation	Ning Zhu, Albert C.S. Chung	In this paper, we propose a graph-based method for 3D vessel tree structure segmentation based on a new tubularity Markov tree model (TMT ), which works as both new energy function and graph construction method.
40	Fast Convolutional Sparse Coding	Hilton Bristow, Anders Eriksson, Simon Lucey	In this paper, we draw upon ideas from signal processing and Augmented Lagrange Methods (ALMs) to produce a fast algorithm with globally optimal subproblems and super-linear convergence.
41	Block and Group Regularized Sparse Modeling for Dictionary Learning	Yu-Tseh Chi, Mohsen Ali, Ajit Rajwade, Jeffrey Ho	This paper proposes a dictionary learning framework that combines the proposed block/group (BGSC) or reconstructed block/group (R-BGSC) sparse coding schemes with the novel Intra-block Coherence Suppression Dictionary Learning (ICS-DL) algorithm.
42	Compressed Hashing	Yue Lin, Rong Jin, Deng Cai, Shuicheng Yan, Xuelong Li	To address this challenge, in this paper we propose a novel approach called Compressed Hashing by exploring the techniques of sparse coding and compressed sensing.
43	Part Discovery from Partial Correspondence	Subhransu Maji, Gregory Shakhnarovich	We propose a learning framework for automatic discovery of parts in such weakly supervised settings, and show the utility of the rich part library learned in this way for three tasks: object detection, category-specific saliency estimation, and fine-grained image parsing.
44	Alternating Decision Forests	Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof	This paper introduces a novel classification method termed Alternating Decision Forests (ADFs), which formulates the training of Random Forests explicitly as a global loss minimization problem.
45	SWIGS: A Swift Guided Sampling Method	Victor Fragoso, Matthew Turk	We present SWIGS, a Swift and efficient Guided Sampling method for robust model estimation from image feature correspondences.
46	Recognize Human Activities from Partially Observed Videos	Yu Cao, Daniel Barrett, Andrei Barbu, Siddharth Narayanaswamy, Haonan Yu, Aaron Michaux, Yuewei Lin, Sven Dickinson, Jeffrey Mark Siskind, Song Wang	In this paper, we propose a new method that can recognize human activities from partially observed videos in the general case.
47	A Convex Regularizer for Reducing Color Artifact in Color Image Recovery	Shunsuke Ono, Isao Yamada	We propose a new convex regularizer, named the local color nuclear norm (LCNN), for color image recovery.
48	Maximum Cohesive Grid of Superpixels for Fast Object Localization	Liang Li, Wei Feng, Liang Wan, Jiawan Zhang	For this purpose, we aim at constructing maximum cohesive SP-grid, which is composed of real nodes, i.e. SPs, and dummy nodes that are meaningless in the image with only position-taking function in the grid.
49	Action Recognition by Hierarchical Sequence Summarization	Yale Song, Louis-Philippe Morency, Randall Davis	Motivated by the observation that human activity data contains information at various temporal resolutions, we present a hierarchical sequence summarization approach for action recognition that learns multiple layers of discriminative feature representations at different temporal granularities.
50	An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision	Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock	Natural image statistics indicate that we should use nonconvex norms for most regularization tasks in image processing and computer vision.
51	Ensemble Video Object Cut in Highly Dynamic Scenes	Xiaobo Ren, Tony X. Han, Zhihai He	We propose a foreground salience graph (FSG) to characterize the similarity of an image patch to the bag-of-words background models in the temporal domain and to neighboring image patches in the spatial domain.
52	Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets	Aurelien Lucchi, Yunpeng Li, Pascal Fua	We propose a working set based approximate subgradient descent algorithm to minimize the margin-sensitive hinge loss arising from the soft constraints in max-margin learning frameworks, such as the structured SVM.
53	Exploring Implicit Image Statistics for Visual Representativeness Modeling	Xiaoshuai Sun, Xin-Jing Wang, Hongxun Yao, Lei Zhang	In this paper, we propose a computational model of visual representativeness by integrating cognitive theories of representativeness heuristics with computer vision and machine learning techniques.
54	Reconstructing Gas Flows Using Light-Path Approximation	Yu Ji, Jinwei Ye, Jingyi Yu	We present a novel computational imaging solution by exploiting the light field probe (LFProbe).
55	Learning Multiple Non-linear Sub-spaces Using K-RBMs	Siddhartha Chandra, Shailesh Kumar, C.V. Jawahar	In this paper, we describe a feature learning scheme for natural images.
56	Articulated and Restricted Motion Subspaces and Their Signatures	Bastien Jacquet, Roland Angst, Marc Pollefeys	Hence, in this paper, a novel theory to analyse relative transformations between two motion-restricted parts will be presented.
57	Simultaneous Active Learning of Classifiers & Attributes via Relative Feedback	Arijit Biswas, Devi Parikh	In this work, we propose three improvements over this set-up.
58	Monocular Template-Based 3D Reconstruction of Extensible Surfaces with Local Linear Elasticity	Abed Malti, Richard Hartley, Adrien Bartoli, Jae-Hak Kim	We propose a new approach for template-based extensible surface reconstruction from a single view.
59	Multi-view Photometric Stereo with Spatially Varying Isotropic Materials	Zhenglong Zhou, Zhe Wu, Ping Tan	We present a method to capture both 3D shape and spatially varying reflectance with a multi-view photometric stereo technique that works for general isotropic materials.
60	A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems	Byung-Woo Hong, Zhaojin Lu, Ganesh Sundaramoorthi	In this work, we address the multi-label Mumford-Shah problem, i.e., the problem of jointly estimating a partitioning of the domain of the image, and functions defined within regions of the partition.
61	Kernel Learning for Extrinsic Classification of Manifold Features	Raviteja Vemulapalli, Jaishanker K. Pillai, Rama Chellappa	In this paper, we address the issue of kernelselection for the classification of features that lie on Riemannian manifolds using the kernel learning approach.
62	Finding Things: Image Parsing with Regions and Per-Exemplar Detectors	Joseph Tighe, Svetlana Lazebnik	This paper presents a system for image parsing, or labeling each pixel in an image with its semantic category, aimed at achieving broad coverage across hundreds of object categories, many of them sparsely sampled.
63	Complex Event Detection via Multi-source Video Attributes	Zhigang Ma, Yi Yang, Zhongwen Xu, Shuicheng Yan, Nicu Sebe, Alexander G. Hauptmann	Hence, we propose to leverage attributes at video level (named as video attributes in this work), i.e., the semantic labels of external videos are used as attributes.
64	Learning Collections of Part Models for Object Recognition	Ian Endres, Kevin J. Shih, Johnston Jiaa, Derek Hoiem	We propose a method to learn a diverse collection of discriminative parts from object bounding box annotations.
65	FrameBreak: Dramatic Image Extrapolation by Guided Shift-Maps	Yinda Zhang, Jianxiong Xiao, James Hays, Ping Tan	To handle this increase in complexity, we introduce a hierarchical graph optimization method to choose the optimal transformation at each output pixel.
66	Bayesian Grammar Learning for Inverse Procedural Modeling	Andelo Martinovic, Luc Van Gool	We present an approach to automatically learn two-dimensional attributed stochastic context-free grammars (2D-ASCFGs) from a set of labeled building facades.
67	Single Image Calibration of Multi-axial Imaging Systems	Amit Agrawal, Srikumar Ramalingam	We present a fully automatic approach using a single photo of a 2D calibration grid.
68	3D R Transform on Spatio-temporal Interest Points for Action Recognition	Chunfeng Yuan, Xi Li, Weiming Hu, Haibin Ling, Stephen Maybank	In this paper, we propose a new global feature to capture the detailed geometrical distribution of interest points.
69	First-Person Activity Recognition: What Are They Doing to Me?	Michael S. Ryoo, Larry Matthies	The paper investigates multichannel kernels to integrate global and local motion information, and presents a new activity learning/recognition methodology that explicitly considers temporal structures displayed in first-person activity videos.
70	Sparse Subspace Denoising for Image Manifolds	Bo Wang, Zhuowen Tu	Experiments carried out on both toy and real applications demonstrate the effectiveness of our method; it is insensitive to parameter tuning and we show significant improvement over the competing algorithms.
71	Adding Unlabeled Samples to Categories by Learned Attributes	Jonghyun Choi, Mohammad Rastegari, Ali Farhadi, Larry S. Davis	We propose a method to expand the visual coverage of training sets that consist of a small number of labeled examples using learned attributes.
72	Auxiliary Cuts for General Classes of Higher Order Functionals	Ismail Ben Ayed, Lena Gorelick, Yuri Boykov	In this study, we derive general bounds for a broad class of higher order functionals.
73	Template-Based Isometric Deformable 3D Reconstruction with Sampling-Based Focal Length Self-Calibration	Adrien Bartoli, Toby Collins	We propose (i) a general variational framework that applies to (calibrated and uncalibrated) general camera models and (ii) self-calibrating 3D reconstruction algorithms for the weak-perspective and full-perspective camera models.
74	Binary Code Ranking with Weighted Hamming Distance	Lei Zhang, Yongdong Zhang, Jinhu Tang, Ke Lu, Qi Tian	In this paper, we propose a weighted Hamming distance ranking algorithm (WhRank) to rank the binary codes of hashing methods.
75	Video Editing with Temporal, Spatial and Appearance Consistency	Xiaojie Guo, Xiaochun Cao, Xiaowu Chen, Yi Ma	The proposed method effectively seeks an optimal solution to simultaneously deal with temporal alignment, pose rectification, as well as precise recovery of the occlusion.
76	Unsupervised Joint Object Discovery and Segmentation in Internet Images	Michael Rubinstein, Armand Joulin, Johannes Kopf, Ce Liu	We present a new unsupervised algorithm to discover and segment out common objects from large and diverse image collections.
77	Learning SURF Cascade for Fast and Accurate Object Detection	Jianguo Li, Yimin Zhang	This paper presents a novel learning framework for training boosting cascade based object detector from large scale dataset.
78	Efficient Computation of Shortest Path-Concavity for 3D Meshes	Henrik Zimmer, Marcel Campen, Leif Kobbelt	In this paper we propose an efficient and straight forward approximation of the Shortest Path-Concavity measure to 3D meshes.
79	Learning Discriminative Illumination and Filters for Raw Material Classification with Optimal Projections of Bidirectional Texture Functions	Chao Liu, Geifei Yang, Jinwei Gu	We present a computational imaging method for raw material classification using features of Bidirectional Texture Functions (BTF).
80	Illumination Estimation Based on Bilayer Sparse Coding	Bing Li, Weihua Xiong, Weiming Hu, Houwen Peng	In this paper, we propose a novel bilayer sparse coding model for illumination estimation that considers image similarity in terms of both low level color distribution and high level image scene content simultaneously.
81	Leveraging Structure from Motion to Learn Discriminative Codebooks for Scalable Landmark Classification	Alessandro Bergamo, Sudipta N. Sinha, Lorenzo Torresani	In this paper we propose a new technique for learning a discriminative codebook for local feature descriptors, specifically designed for scalable landmark classification.
82	Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition	Qiang Hao, Rui Cai, Zhiwei Li, Lei Zhang, Yanwei Pang, Feng Wu, Yong Rui	To overcome this scalability bottleneck, we propose an efficient 2D-to-3D correspondence filtering approach, which combines a light-weight neighborhoodbased step with a finer-grained pairwise step to remove spurious correspondences based on 2D/3D geometric cues.
83	Weakly Supervised Learning for Attribute Localization in Outdoor Scenes	Shuo Wang, Jungseock Joo, Yizhou Wang, Song-Chun Zhu	In this paper, we propose a weakly supervised method for simultaneously learning scene parts and attributes from a collection of images associated with attributes in text, where the precise localization of the each attribute left unknown.
84	Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines	Gunhee Kim, Eric P. Xing	In this paper, as a first technical step to detect such collective storylines, we propose an approach to jointly aligning and segmenting uncalibrated multiple photo streams.
85	Studying Relationships between Human Gaze, Description, and Computer Vision	Kiwon Yun, Yifan Peng, Dimitris Samaras, Gregory J. Zelinsky, Tamara L. Berg	In this paper, we conduct experiments to better understand the relationship between images, the eye movements people make while viewing images, and how people construct natural language to describe images.
86	SLAM++: Simultaneous Localisation and Mapping at the Level of Objects	Renato F. Salas-Moreno, Richard A. Newcombe, Hauke Strasdat, Paul H.J. Kelly, Andrew J. Davison	We present the major advantages of a new ‘object oriented’ 3D SLAM paradigm, which takes full advantage in the loop of prior knowledge that many scenes consist of repeated, domain-specific objects and structures.
87	A Theory of Refractive Photo-Light-Path Triangulation	Visesh Chari, Peter Sturm	In this paper, we describe a method that combines both geometric and radiometric information to do reconstruction.
88	Learning Structured Low-Rank Representations for Image Classification	Yangmuzi Zhang, Zhuolin Jiang, Larry S. Davis	An approach to learn a structured low-rank representation for image classification is presented.
89	Detecting and Aligning Faces by Image Retrieval	Xiaohui Shen, Zhe Lin, Jonathan Brandt, Ying Wu	In order to overcome these challenges, we present a novel and robust exemplarbased face detector that integrates image retrieval and discriminative learning.
90	Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification	Ajay Kumar, Cyril Kwong	Multiple 2D fingerprint images (with varying illumination profile) acquired to build 3D fingerprints can themselves be used recover 2D features for further improving 3D fingerprint identification and has been illustrated in this paper.
91	Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling	Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik Learned-Miller	In this work, we present a new model that uses the combined power of these two network types to build a state-of-the-art labeler.
92	It’s Not Polite to Point: Describing People with Uncertain Attributes	Amir Sadovnik, Andrew Gallagher, Tsuhan Chen	We introduce an efficient, principled method for choosing which attributes are included in a short description to maximize the likelihood that a third party will correctly guess to which person the description refers.
93	Reconstructing Loopy Curvilinear Structures Using Integer Programming	Engin Turetken, Fethallah Benmansour, Bjoern Andres, Hanspeter Pfister, Pascal Fua	We propose a novel approach to automated delineation of linear structures that form complex and potentially loopy networks.
94	Weakly-Supervised Dual Clustering for Image Semantic Segmentation	Yang Liu, Jing Liu, Zechao Li, Jinhui Tang, Hanqing Lu	In this paper, we propose a novel Weakly-Supervised Dual Clustering (WSDC) approach for image semantic segmentation with image-level labels, i.e., collaboratively performing image segmentation and tag alignment with those regions.
95	Multi-target Tracking by Rank-1 Tensor Approximation	Xinchu Shi, Haibin Ling, Junling Xing, Weiming Hu	In this paper we formulate multi-target tracking (MTT) as a rank-1 tensor approximation problem and propose an 1 norm tensor power iteration solution.
96	Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior	Haichao Zhang, David Wipf, Yanning Zhang	This paper presents a robust algorithm for estimating a single latent sharp image given multiple blurry and/or noisy observations.
97	Templateless Quasi-rigid Shape Modeling with Implicit Loop-Closure	Ming Zeng, Jiaxiang Zheng, Xuan Cheng, Xinguo Liu	This paper presents a method for quasi-rigid objects modeling from a sequence of depth scans captured at different time instances.
98	Cross-View Action Recognition via a Continuous Virtual Path	Zhong Zhang, Chunheng Wang, Baihua Xiao, Wen Zhou, Shuang Liu, Cunzhao Shi	In this paper, we propose a novel method for cross-view action recognition via a continuous virtual path which connects the source view and the target view.
99	Non-rigid Structure from Motion with Diffusion Maps Prior	Lili Tao, Bogdan J. Matuszewski	In this paper, a novel approach based on a non-linear manifold learning technique is proposed to recover 3D nonrigid structures from 2D image sequences captured by a single camera.
100	Discriminative Non-blind Deblurring	Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, Stefan Roth	We address this gap by proposing a discriminative approach for non-blind deblurring.
101	Prostate Segmentation in CT Images via Spatial-Constrained Transductive Lasso	Yinghuan Shi, Shu Liao, Yaozong Gao, Daoqiang Zhang, Yang Gao, Dinggang Shen	In this paper, a novel semi-automated prostate segmentation method is presented.
102	Optimized Pedestrian Detection for Multiple and Occluded People	Sitapa Rujikietgumjorn, Robert T. Collins	We present a quadratic unconstrained binary optimization (QUBO) framework for reasoning about multiple object detections with spatial overlaps.
103	Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination	Laurent Sifre, Stephane Mallat	Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination
104	A Minimum Error Vanishing Point Detection Approach for Uncalibrated Monocular Images of Man-Made Environments	Yiliang Xu, Sangmin Oh, Anthony Hoogs	We present a novel vanishing point detection algorithm for uncalibrated monocular images of man-made environments.
105	Poselet Key-Framing: A Model for Human Activity Recognition	Michalis Raptis, Leonid Sigal	In this paper, we develop a new model for recognizing human actions.
106	Probabilistic Label Trees for Efficient Large Scale Image Classification	Baoyuan Liu, Fereshteh Sadeghi, Marshall Tappen, Ohad Shamir, Ce Liu	In this paper, we show how the parameters of the label tree can be found using maximum likelihood estimation.
107	Depth Super Resolution by Rigid Body Self-Similarity in 3D	Michael Hornacek, Christoph Rhemann, Margrit Gelautz, Carsten Rother	In support of obtaining a dense correspondence field in reasonable time, we introduce a new 3D variant of PatchMatch. In stark contrast to earlier work, we make no use of ancillary data like a color image at the target resolution, multiple aligned depth maps, or a database of highresolution depth exemplars.
108	SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning	David Weiss, Ben Taskar	We propose SCALPEL, a flexible method for object segmentation that integrates rich region-merging cues with midand high-level information about object layout, class, and scale into the segmentation process.
109	Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization	Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun	In this paper we propose an affordable solution to selflocalization, which utilizes visual odometry and road maps as the only inputs.
110	Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories	Michele Fenzi, Laura Leal-Taixe, Bodo Rosenhahn, Jorn Ostermann	In this paper, we propose a method for learning a class representation that can return a continuous value for the pose of an unknown class instance using only 2D data and weak 3D labelling information.
111	Event Retrieval in Large Video Collections with Circulant Temporal Encoding	Jerome Revaud, Matthijs Douze, Cordelia Schmid, Herve Jegou	This paper presents an approach for large-scale event retrieval. Finally, we introduce a challenging dataset for event retrieval, EVVE, and report the performance on this dataset.
112	Looking Beyond the Image: Unsupervised Learning for Object Saliency and Detection	Parthipan Siva, Chris Russell, Tao Xiang, Lourdes Agapito	We propose a principled probabilistic formulation of object saliency as a sampling problem.
113	Selective Transfer Machine for Personalized Facial Action Unit Detection	Wen-Sheng Chu, Fernando De La Torre, Jeffery F. Cohn	We introduce a transductive learning method, which we refer to Selective Transfer Machine (STM), to personalize a generic classifier by attenuating person-specific biases.
114	Procrustean Normal Distribution for Non-rigid Structure from Motion	Minsik Lee, Jungchan Cho, Chong-Ho Choi, Songhwai Oh	In this paper, we propose new constraints that are more effective for non-rigid shape recovery.
115	Blur Processing Using Double Discrete Wavelet Transform	Yi Zhang, Keigo Hirakawa	We propose a notion of double discrete wavelet transform (DDWT) that is designed to sparsify the blurred image and the blur kernel simultaneously.
116	Video Enhancement of People Wearing Polarized Glasses: Darkening Reversal and Reflection Reduction	Mao Ye, Cha Zhang, Ruigang Yang	This paper presents a computational framework to reduce undesirable artifacts in the eye regions caused by these 3D glasses.
117	Joint Geodesic Upsampling of Depth Images	Ming-Yu Liu, Oncel Tuzel, Yuichi Taguchi	We propose an algorithm utilizing geodesic distances to upsample a low resolution depth image using a registered high resolution color image.
118	Discriminative Re-ranking of Diverse Segmentations	Payman Yadollahpour, Dhruv Batra, Gregory Shakhnarovich	This paper introduces a two-stage approach to semantic image segmentation.
119	Incorporating User Interaction and Topological Constraints within Contour Completion via Discrete Calculus	Jia Xu, Maxwell D. Collins, Vikas Singh	We study the problem of interactive segmentation and contour completion for multiple objects.
120	Shading-Based Shape Refinement of RGB-D Images	Lap-Fai Yu, Sai-Kit Yeung, Yu-Wing Tai, Stephen Lin	We present a shading-based shape refinement algorithm which uses a noisy, incomplete depth map from Kinect to help resolve ambiguities in shape-from-shading.
121	Active Contours with Group Similarity	Xiaowei Zhou, Xiaojie Huang, James S. Duncan, Weichuan Yu	In this paper, we propose to use the group similarity of object shapes in multiple images as a prior to aid segmentation, which can be interpreted as an unsupervised approach of shape prior modeling.
122	Diffusion Processes for Retrieval Revisited	Michael Donoser, Horst Bischof	In this paper we revisit diffusion processes on affinity graphs for capturing the intrinsic manifold structure defined by pairwise affinity matrices.
123	From N to N+1: Multiclass Transfer Incremental Learning	Ilja Kuzborskij, Francesco Orabona, Barbara Caputo	The contribution of this paper is a discriminative method that addresses this issue, based on a Least-Squares Support Vector Machine formulation.
124	The SVM-Minus Similarity Score for Video Face Recognition	Lior Wolf, Noga Levy	The method we propose belongs to a family of classifierbased similarity scores.
125	Human Pose Estimation Using Body Parts Dependent Joint Regressors	Matthias Dantone, Juergen Gall, Christian Leistner, Luc Van Gool	In this work, we address the problem of estimating 2d human pose from still images.
126	A Principled Deep Random Field Model for Image Segmentation	Pushmeet Kohli, Anton Osokin, Stefanie Jegelka	We discuss a model for image segmentation that is able to overcome the short-boundary bias observed in standard pairwise random field based approaches.
127	Hash Bit Selection: A Unified Solution for Selection Problems in Hashing	Xianglong Liu, Junfeng He, Bo Lang, Shih-Fu Chang	In this work, we unify all these selection problems into a hash bit selection framework, i.e. selecting the most informative hash bits from a pool of candidate bits generated by different types of hashing methods using different feature spaces and/or parameter settings, etc.
128	HON4D: Histogram of Oriented 4D Normals for Activity Recognition from Depth Sequences	Omar Oreifej, Zicheng Liu	We present a new descriptor for activity recognition from videos acquired by a depth sensor.
129	Principal Observation Ray Calibration for Tiled-Lens-Array Integral Imaging Display	Weiming Li, Haitao Wang, Mingcai Zhou, Shandong Wang, Shaohui Jiao, Xing Mei, Tao Hong, Hoyoung Lee, Jiyeun Kim	In this paper, we propose a novel calibration method based on defining a set of principle observation rays that pass lens centers of the TLA and the camera’s optical center.
130	Exploring Weak Stabilization for Motion Feature Extraction	Dennis Park, C. L. Zitnick, Deva Ramanan, Piotr Dollar	We describe a combined approach that uses coarse-scale flow and fine-scale temporal difference features.
131	Discovering the Structure of a Planar Mirror System from Multiple Observations of a Single Point	Ilya Reshetouski, Alkhazur Manakov, Ayush Bandhari, Ramesh Raskar, Hans-Peter Seidel, Ivo Ihrke	To counter the situation, we propose theoretically devised geometric constraints that enable an efficient pruning of the solution space and develop a heuristic randomized search algorithm that uses these constraints to obtain an effective solution.
132	Fine-Grained Crowdsourcing for Fine-Grained Recognition	Jia Deng, Jonathan Krause, Li Fei-Fei	In this work, we include humans in the loop to help computers select discriminative features.
133	Joint 3D Scene Reconstruction and Class Segmentation	Christian Hane, Christopher Zach, Andrea Cohen, Roland Angst, Marc Pollefeys	In this paper we argue that image segmentation and dense 3D reconstruction contribute valuable information to each other’s task.
134	Kernel Null Space Methods for Novelty Detection	Paul Bodesheim, Alexander Freytag, Erik Rodner, Michael Kemmler, Joachim Denzler	We present how to apply a null space method for novelty detection, which maps all training samples of one class to a single point.
135	Information Consensus for Distributed Multi-target Tracking	Ahmed T. Kamal, Jay A. Farrell, Amit K. Roy-Chowdhury	In this paper, we propose consensus-based distributed multi-target tracking algorithms in a camera network that are designed to address this issue of naivety.
136	CLAM: Coupled Localization and Mapping with Efficient Outlier Handling	Jonathan Balzer, Stefano Soatto	We describe a method to efficiently generate a model (map) of small-scale objects from video. We have collected a new dataset to benchmark model building in the small scale, which we test our algorithm on in comparison to others.
137	Semi-supervised Domain Adaptation with Instance Constraints	Jeff Donahue, Judy Hoffman, Erik Rodner, Kate Saenko, Trevor Darrell	We propose a general framework for adapting classifiers from “borrowed” data to the target domain using a combination of available labeled and unlabeled examples.
138	Detecting and Naming Actors in Movies Using Generative Appearance Models	Vineet Gandhi, Remi Ronfard	We introduce a generative model for learning person and costume specific detectors from labeled examples.
139	Rolling Shutter Camera Calibration	Luc Oth, Paul Furgale, Laurent Kneip, Roland Siegwart	We present a new method that only requires video of a known calibration pattern.
140	A Linear Approach to Matching Cuboids in RGBD Images	Hao Jiang, Jianxiong Xiao	We propose a novel linear method to match cuboids in indoor scenes using RGBD images from Kinect.
141	Discriminative Segment Annotation in Weakly Labeled Video	Kevin Tang, Rahul Sukthankar, Jay Yagnik, Li Fei-Fei	We present CRANE, a weakly supervised algorithm that is specifically designed to learn under such conditions.
142	Multi-agent Event Detection: Localization and Role Assignment	Suha Kwak, Bohyung Han, Joon Hee Han	We present a joint estimation technique of event localization and role assignment when the target video event is described by a scenario.
143	Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection	Xiaolong Wang, Liang Lin, Lichao Huang, Shuicheng Yan	This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects with large variation in appearance.
144	Correspondence-Less Non-rigid Registration of Triangular Surface Meshes	Zsolt Santa, Zoltan Kato	A novel correspondence-less approach is proposed to find a thin plate spline map between a pair of deformable 3D objects represented by triangular surface meshes.
145	Globally Consistent Multi-label Assignment on the Ray Space of 4D Light Fields	Sven Wanner, Christoph Straehle, Bastian Goldluecke	We present the first variational framework for multi-label segmentation on the ray space of 4D light fields.
146	Top-Down Segmentation of Non-rigid Visual Objects Using Derivative-Based Search on Sparse Manifolds	Jacinto C. Nascimento, Gustavo Carneiro	In this paper, we propose the use of sparse manifolds to reduce the dimensionality of the rigid detection search space of current stateof-the-art top-down segmentation methodologies.
147	Harry Potter’s Marauder’s Map: Localizing and Tracking Multiple Persons-of-Interest by Nonnegative Discretization	Shoou-I Yu, Yi Yang, Alexander Hauptmann	We propose a tracking-by-detection approach with nonnegative discretization to tackle this problem.
148	Fast Image Super-Resolution Based on In-Place Example Regression	Jianchao Yang, Zhe Lin, Scott Cohen	We propose a fast regression model for practical single image super-resolution based on in-place examples, by leveraging two fundamental super-resolution approaches-learning from an external database and learning from selfexamples.
149	Query Adaptive Similarity for Large Scale Object Retrieval	Danfeng Qin, Christian Wengert, Luc Van Gool	In this paper we present a probabilistic framework for modeling the feature to feature similarity measure.
150	Winding Number for Region-Boundary Consistent Salient Contour Extraction	Yansheng Ming, Hongdong Li, Xuming He	In this paper we show how to combine both cues in a unified framework.
151	Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance	Shireen Y. Elhabian, Aly A. Farag	In this paper, we propose an analytic formulation for low-dimensional subspace construction in which shading cues lie while preserving the natural structure of an image sample.
152	A Fully-Connected Layered Model of Foreground and Background Flow	Deqing Sun, Jonas Wulff, Erik B. Sudderth, Hanspeter Pfister, Michael J. Black	To address this, we formulate a fully-connected layered model that enables global reasoning about the complicated segmentations of real objects.
153	Bilinear Programming for Human Activity Recognition with Unknown MRF Graphs	Zhenhua Wang, Qinfeng Shi, Chunhua Shen, Anton van den Hengel	We apply our techniques to predict sport moves (such as serve, volley in tennis) and human activity in TV episodes (such as kiss, hug and Hi-Five).
154	What Object Motion Reveals about Shape with Unknown BRDF and Lighting	Manmohan Chandraker, Dikpal Reddy, Yizhou Wang, Ravi Ramamoorthi	We present a theory that addresses the problem of determining shape from the (small or differential) motion of an object with unknown isotropic reflectance, under arbitrary unknown distant illumination, for both orthographic and perpsective projection.
155	Learning by Associating Ambiguously Labeled Images	Zinan Zeng, Shijie Xiao, Kui Jia, Tsung-Han Chan, Shenghua Gao, Dong Xu, Yi Ma	We study in this paper the problem of learning classifiers from ambiguously labeled images.
156	As-Projective-As-Possible Image Stitching with Moving DLT	Julio Zaragoza, Tat-Jun Chin, Michael S. Brown, David Suter	To this end we propose as-projective-as-possible warps, i.e., warps that aim to be globally projective, yet allow local non-projective deviations to account for violations to the assumed imaging conditions.
157	Light Field Distortion Feature for Transparent Object Recognition	Kazuki Maeno, Hajime Nagahara, Atsushi Shimada, Rin-Ichiro Taniguchi	In this paper, we use a single-shot light Aeld image as an input and model the distortion of the light Aeld caused by the refractive property of a transparent object.
158	Ensemble Learning for Confidence Measures in Stereo Vision	Ralf Haeusler, Rahul Nair, Daniel Kondermann	With the aim to improve accuracy of stereo confidence measures, we apply the random decision forest framework to a large set of diverse stereo confidence measures.
159	Mirror Surface Reconstruction from a Single Image	Miaomiao Liu, Richard Hartley, Mathieu Salzmann	In this scenario, we formulate reconstruction as an optimization problem, which can be solved using a nonlinear least-squares method.
160	Handling Noise in Single Image Deblurring Using Directional Filters	Lin Zhong, Sunghyun Cho, Dimitris Metaxas, Sylvain Paris, Jue Wang	We propose a new method for handling noise in blind image deconvolution based on new theoretical and practical insights.
161	Joint Spectral Correspondence for Disparate Image Matching	Mayank Bansal, Kostas Daniilidis	We propose a novel formulation for detecting and matching persistent features between such images by analyzing the eigen-spectrum of the joint image graph constructed from all the pixels in the two images.
162	From Local Similarity to Global Coding: An Application to Image Classification	Amirreza Shaban, Hamid R. Rabiee, Mehrdad Farajtabar, Marjan Ghazvininejad	In this paper, we propose a coding scheme that brings into focus the manifold structure of descriptors, and devise a method to compute the global similarities of descriptors to the bases.
163	Probabilistic Elastic Matching for Pose Variant Face Verification	Haoxiang Li, Gang Hua, Zhe Lin, Jonathan Brandt, Jianchao Yang	We approach this problem through a probabilistic elastic matching method.
164	Story-Driven Summarization for Egocentric Video	Zheng Lu, Kristen Grauman	We present a video summarization approach that discovers the story of an egocentric video.
165	Towards Pose Robust Face Recognition	Dong Yi, Zhen Lei, Stan Z. Li	In this paper, we propose a novel method for pose robust face recognition towards practical applications, which is fast, pose robust and can work well under unconstrained environments.
166	All About VLAD	Relja Arandjelovic, Andrew Zisserman	The objective of this paper is large scale object instance retrieval, given a query image.
167	Graph-Based Discriminative Learning for Location Recognition	Song Cao, Noah Snavely	In particular, starting from a graph on a set of images based on visual connectivity, we propose a method for selecting a set of subgraphs and learning a local distance function for each using discriminative techniques.
168	Calibrating Photometric Stereo by Holistic Reflectance Symmetry Analysis	Zhe Wu, Ping Tan	We develop a simple algorithm of auto-calibration from separable homogeneous specular reflection of real images.
169	Relative Hidden Markov Models for Evaluating Motion Skill	Qiang Zhang, Baoxin Li	Our focus in this paper is on videobased surgical training, in which a key task is to rate the performance of a trainee based on a video capturing his motion.
170	Classification of Tumor Histology via Morphometric Context	Hang Chang, Alexander Borowsky, Paul Spellman, Bahram Parvin	In this paper, we propose two algorithms for classification of tissue histology based on robust representations of morphometric context, which are built upon nuclear level morphometric features at various locations and scales within the spatial pyramid matching (SPM) framework.
171	Five Shades of Grey for Fast and Reliable Camera Pose Estimation	Adam Herout, Istvan Szentandrasi, Michal Zacharias, Marketa Dubska, Rudolf Kajan	We introduce here an improved design of the Uniform Marker Fields and an algorithm for their fast and reliable detection.
172	Fast Patch-Based Denoising Using Approximated Patch Geodesic Paths	Xiaogang Chen, Sing Bing Kang, Jie Yang, Jingyi Yu	In this paper, we present a novel fast patch-based denoising technique based on Patch Geodesic Paths (PatchGP).
173	Boosting Binary Keypoint Descriptors	Tomasz Trzcinski, Mario Christoudias, Pascal Fua, Vincent Lepetit	In this paper, we propose a novel framework to learn an extremely compact binary descriptor we call BinBoost that is very robust to illumination and viewpoint changes.
174	Structured Face Hallucination	Chih-Yuan Yang, Sifei Liu, Ming-Hsuan Yang	In contrast to existing methods based on patch similarity or holistic constraints in the image space, we propose to exploit local image structures for face hallucination.
175	Adaptive Active Learning for Image Classification	Xin Li, Yuhong Guo	In this paper, we present a novel adaptive active learning approach that combines an information density measure and a most uncertainty measure together to select critical instances to label for image classifications.
176	Improving an Object Detector and Extracting Regions Using Superpixels	Guang Shu, Afshin Dehghan, Mubarak Shah	We propose an approach to improve the detection performance of a generic detector when it is applied to a particular video.
177	HDR Deghosting: How to Deal with Saturation?	Jun Hu, Orazio Gallo, Kari Pulli, Xiaobai Sun	We present a novel method for aligning images in an HDR (high-dynamic-range) image stack to produce a new exposure stack where all the images are aligned and appear as if they were taken simultaneously, even in the case of highly dynamic scenes.
178	Transfer Sparse Coding for Robust Image Representation	Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Yuchen Guo, Philip S. Yu	In this paper, we propose a Transfer Sparse Coding (TSC) approach to construct robust sparse representations for classifying cross-distribution images accurately.
179	Semi-supervised Learning of Feature Hierarchies for Object Detection in a Video	Yang Yang, Guang Shu, Mubarak Shah	We propose a novel approach to boost the performance of generic object detectors on videos by learning videospecific features using a deep neural network.
180	Computationally Efficient Regression on a Dependency Graph for Human Pose Estimation	Kota Hara, Rama Chellappa	We present a hierarchical method for human pose estimation from a single still image.
181	In Defense of Sparsity Based Face Recognition	Weihong Deng, Jiani Hu, Jun Guo	This paper challenges the prevailing view by proposing a “prototype plus variation” representation model for sparsity based face recognition.
182	Image Matting with Local and Nonlocal Smooth Priors	Xiaowu Chen, Dongqing Zou, Steven Zhiying Zhou, Qinping Zhao, Ping Tan	In this paper we propose a novel alpha matting method with local and nonlocal smooth priors.
183	Image Tag Completion via Image-Specific and Tag-Specific Linear Sparse Reconstructions	Zijia Lin, Guiguang Ding, Mingqing Hu, Jianmin Wang, Xiaojun Ye	In this paper, we propose a novel scheme denoted as LSR for automatic image tag completion via image-specific and tag-specific Linear Sparse Reconstructions.
184	Non-parametric Filtering for Geometric Detail Extraction and Material Representation	Zicheng Liao, Jason Rock, Yang Wang, David Forsyth	In this work, we explore using a non-parametric method to separate geometric detail from intrinsic image components.
185	Bottom-Up Segmentation for Top-Down Detection	Sanja Fidler, Roozbeh Mottaghi, Alan Yuille, Raquel Urtasun	In this paper we are interested in how semantic segmentation can help object detection.
186	Expanded Parts Model for Human Attribute and Action Recognition in Still Images	Gaurav Sharma, Frederic Jurie, Cordelia Schmid	We propose a new model for recognizing human attributes (e.g. wearing a suit, sitting, short hair) and actions (e.g. running, riding a horse) in still images.
187	Inductive Hashing on Manifolds	Fumin Shen, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, Zhenmin Tang	In this work, we consider how to learn compact binary embeddings on their intrinsic manifolds.
188	Robust Feature Matching with Alternate Hough and Inverted Hough Transforms	Hsin-Yi Chen, Yen-Yu Lin, Bing-Yu Chen	We present an algorithm that carries out alternate Hough transform and inverted Hough transform to establish feature correspondences, and enhances the quality of matching in both precision and recall.
189	Fast Object Detection with Entropy-Driven Evaluation	Raphael Sznitman, Carlos Becker, Francois Fleuret, Pascal Fua	We introduce an alternative approach to speeding-up classifier evaluation which overcomes these limitations.
190	Event Recognition in Videos by Learning from Heterogeneous Web Sources	Lin Chen, Lixin Duan, Dong Xu	In this work, we propose to leverage a large number of loosely labeled web videos (e.g., from YouTube) and web images (e.g., from Google/Bing image search) for visual event recognition in consumer videos without requiring any labeled consumer videos.
191	Discriminative Color Descriptors	Rahat Khan, Joost van de Weijer, Fahad Shahbaz Khan, Damien Muselet, Christophe Ducottet, Cecile Barat	In this paper we take an information theoretic approach to color description.
192	Optical Flow Estimation Using Laplacian Mesh Energy	Wenbin Li, Darren Cosker, Matthew Brown, Rui Tang	In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration.
193	Constrained Clustering and Its Application to Face Clustering in Videos	Baoyuan Wu, Yifan Zhang, Bao-Gang Hu, Qiang Ji	In this paper, we focus on face clustering in videos.
194	Subcategory-Aware Object Classification	Jian Dong, Wei Xia, Qiang Chen, Jianshi Feng, Zhongyang Huang, Shuicheng Yan	In this paper, we introduce a subcategory-aware object classification framework to boost category level object classification performance.
195	Face Recognition in Movie Trailers via Mean Sequence Sparse Representation-Based Classification	Enrique G. Ortiz, Alan Wright, Mubarak Shah	This paper presents an end-to-end video face recognition system, addressing the difficult problem of identifying a video face track using a large dictionary of still face images of a few hundred people, while rejecting unknown individuals. We also introduce a new Movie Trailer Face Dataset collected from 101 movie trailers on YouTube.
196	Multi-attribute Queries: To Merge or Not to Merge?	Mohammad Rastegari, Ali Diba, Devi Parikh, Ali Farhadi	Hence we propose an optimization approach that identifies beneficial conjunctions without explicitly training the corresponding classifier.
197	Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization	Jorg Hendrik Kappes, Markus Speth, Gerhard Reinelt, Christoph Schnorr	In this paper we introduce a promising way to bridge this gap based on partial optimality and structural properties of the underlying problem factorization.
198	Plane-Based Content Preserving Warps for Video Stabilization	Zihan Zhou, Hailin Jin, Yi Ma	To overcome this limitation, in this paper we present a hybrid approach for novel view synthesis, observing that the textureless regions often correspond to large planar surfaces in the scene.
199	Three-Dimensional Bilateral Symmetry Plane Estimation in the Phase Domain	Ramakrishna Kakarala, Prabhu Kaliamoorthi, Vittal Premachandran	We show that bilateral symmetry plane estimation for three-dimensional (3-D) shapes may be carried out accurately, and efficiently, in the spherical harmonic domain.
200	Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots	Chao-Yeh Chen, Kristen Grauman	We propose an approach to learn action categories from static images that leverages prior observations of generic human motion to augment its training process.
201	Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery	Rikke Gade, Anders Jorgensen, Thomas B. Moeslund	We therefore propose a framework that optimises the occupancy analysis over long periods by including information on the transition in occupancy, when people enter or leave the monitored area.
202	Topical Video Object Discovery from Key Frames by Modeling Word Co-occurrence Prior	Gangqiang Zhao, Junsong Yuan, Gang Hua	We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames.
203	Keypoints from Symmetries by Wave Propagation	Samuele Salti, Alessandro Lanza, Luigi Di Stefano	Keypoints from Symmetries by Wave Propagation
204	Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities	Horst Possegger, Sabine Sternig, Thomas Mauthner, Peter M. Roth, Horst Bischof	To overcome these limitations, we introduce the concept of an occupancy volume exploiting the full geometry and the objects’ center of mass and develop an efficient algorithm for 3D object tracking.
205	A Divide-and-Conquer Method for Scalable Low-Rank Latent Matrix Pursuit	Yan Pan, Hanjiang Lai, Cong Liu, Shuicheng Yan	To address this issue, we provide a scalable solution for large-scale low-rank latent matrix pursuit by a divide-andconquer method.
206	PDM-ENLOR: Learning Ensemble of Local PDM-Based Regressions	Yen H. Le, Uday Kurkure, Ioannis A. Kakadiaris	We propose a novel method (dubbed PDM-ENLOR) that overcomes these limitations by locating each shape model point individually using an ensemble of local regression models and appearance cues from selected model points.
207	Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution	Li He, Hairong Qi, Russell Zaretzki	We compare the proposed approach to several state-of-the-art dictionary learning methods by applying this method to single image super-resolution.
208	Fast Trust Region for Segmentation	Lena Gorelick, Frank R. Schmidt, Yuri Boykov	In this paper we propose a Fast Trust Region (FTR) approach for optimization of segmentation energies with nonlinear regional terms, which are known to be challenging for existing algorithms.
209	Area Preserving Brain Mapping	Zhengyu Su, Wei Zeng, Rui Shi, Yalin Wang, Jian Sun, Xianfeng Gu	In the study of cortical surface classification for recognition of Alzheimer’s Disease, the proposed method outperforms some other morphometry features.
210	Multi-level Discriminative Dictionary Learning towards Hierarchical Visual Categorization	Li Shen, Shuhui Wang, Gang Sun, Shuqiang Jiang, Qingming Huang	In this paper, we propose a novel dictionary learning method by taking advantage of hierarchical category correlation.
211	BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification	Takumi Kobayashi	In this paper, we propose a novel feature extraction method for image classification.
212	Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer	Liansheng Zhuang, Allen Y. Yang, Zihan Zhou, S. Shankar Sastry, Yi Ma	We propose a novel face recognition algorithm to address this problem based on a sparse representation based classification (SRC) framework.
213	GeoF: Geodesic Forests for Learning Coupled Predictors	Peter Kontschieder, Pushmeet Kohli, Jamie Shotton, Antonio Criminisi	This paper presents a new and efficient forest based model that achieves spatially consistent semantic image segmentation by encoding variable dependencies directly in the feature space the forests operate on.
214	Improving Image Matting Using Comprehensive Sampling Sets	Ehsan Shahrian, Deepu Rajan, Brian Price, Scott Cohen	In this paper, we present a new image matting algorithm that achieves state-of-the-art performance on a benchmark dataset of images.
215	Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection	Joseph J. Lim, C. L. Zitnick, Piotr Dollar	We propose a novel approach to both learning and detecting local contour-based representations for mid-level features.
216	Subspace Interpolation via Dictionary Learning for Unsupervised Domain Adaptation	Jie Ni, Qiang Qiu, Rama Chellappa	We propose to interpolate subspaces through dictionary learning to link the source and target domains.
217	Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation	Luming Zhang, Mingli Song, Zicheng Liu, Xiao Liu, Jiajun Bu, Chun Chen	In this paper, we present a new weakly supervised image segmentation algorithm by learning the distribution of spatially structured superpixel sets from image-level labels.
218	Fast Energy Minimization Using Learned State Filters	Matthieu Guillaumin, Luc Van Gool, Vittorio Ferrari	In this paper we propose a novel, generic algorithm to approximately minimize any discrete pairwise energy function.
219	Learning Binary Codes for High-Dimensional Data Using Bilinear Projections	Yunchao Gong, Sanjiv Kumar, Henry A. Rowley, Svetlana Lazebnik	We present a novel method for converting such descriptors to compact similarity-preserving binary codes that exploits their natural matrix structure to reduce their dimensionality using compact bilinear projections instead of a single large projection matrix.
220	Multi-scale Curve Detection on Surfaces	Michael Kolomenkin, Ilan Shimshoni, Ayellet Tal	In this paper, we propose a general framework for automatically detecting the optimal scale for each point on the surface.
221	Saliency Aggregation: A Data-Driven Approach	Long Mai, Yuzhen Niu, Feng Liu	Our idea is to use data-driven approaches to saliency aggregation that appropriately consider the performance gaps among individual methods and the performance dependence of each method on individual images.
222	Crossing the Line: Crowd Counting by Integer Programming with Local Features	Zheng Ma, Antoni B. Chan	We propose an integer programming method for estimating the instantaneous count of pedestrians crossing a line of interest in a video sequence.
223	Discriminative Subspace Clustering	Vasileios Zografos, Liam Ellis, Rudolf Mester	We present a novel method for clustering data drawn from a union of arbitrary dimensional subspaces, called Discriminative Subspace Clustering (DiSC).
224	Measuring Crowd Collectiveness	Bolei Zhou, Xiaoou Tang, Xiaogang Wang	By integrating path similarities among crowds on collective manifold, this paper proposes a descriptor of collectiveness and an efficient computation for the crowd and its constituent individuals.
225	MKPLS: Manifold Kernel Partial Least Squares for Lipreading and Speaker Identification	Amr Bakry, Ahmed Elgammal	In this paper, we propose a novel approach for lipreading and speaker identification.
226	Whitened Expectation Propagation: Non-Lambertian Shape from Shading and Shadow	Brian Potetz, Mohammadreza Hajiarbabi	Here, we propose a variation of EP that exploits regularities in natural scene statistics to achieve run times that are linear in both number of pixels and clique size.
227	Multi-class Video Co-segmentation with a Generative Multi-video Model	Wei-Chen Chiu, Mario Fritz	We propose to study multi-class video co-segmentation where the number of object classes is unknown as well as the number of instances in each frame and video.
228	Lp-Norm IDF for Large Scale Image Search	Liang Zheng, Shengjin Wang, Ziqiong Liu, Qi Tian	To tackle this problem, this paper introduces a novel IDF expression by the use of L p -norm pooling technique.
229	Saliency Detection via Graph-Based Manifold Ranking	Chuan Yang, Lihe Zhang, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang	Instead of considering the contrast between the salient objects and their surrounding regions, we consider both foreground and background cues in a different way. We also create a more difficult benchmark database containing 5,172 images to test the proposed saliency model and make this database publicly available with this paper for further studies in the saliency field.
230	Online Object Tracking: A Benchmark	Yi Wu, Jongwoo Lim, Ming-Hsuan Yang	By analyzing quantitative results, we identify effective approaches for robust tracking and provide potential future research directions in this field.
231	Tracking Sports Players with Context-Conditioned Motion Models	Jingchen Liu, Peter Carr, Robert T. Collins, Yanxi Liu	Instead, we introduce a set of Game Context Features extracted from noisy detections to describe the current state of the match, such as how the players are spatially distributed.
232	Physically Plausible 3D Scene Tracking: The Single Actor Hypothesis	Nikolaos Kyriazis, Antonis Argyros	We present the first approach that exploits this observation to perform model-based 3D tracking of a table-top scene comprising passive objects and an active hand.
233	Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces	Shaokang Chen, Conrad Sanderson, Mehrtash T. Harandi, Brian C. Lovell	To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets.
234	Underwater Camera Calibration Using Wavelength Triangulation	Timothy Yau, Minglun Gong, Yee-Hong Yang	We describe how to construct a novel calibration device for our method and evaluate the accuracy of the method through synthetic and real experiments.
235	Expressive Visual Text-to-Speech Using Active Appearance Models	Robert Anderson, Bjorn Stenger, Vincent Wan, Roberto Cipolla	This paper presents a complete system for expressive visual text-to-speech (VTTS), which is capable of producing expressive output, in the form of a ‘talking head’, given an input text and a set of continuous expression weights.
236	Joint Sparsity-Based Representation and Analysis of Unconstrained Activities	Raghuraman Gopalan	We demonstrate the efficacy of our approach for activity classification and clustering by reporting competitive results on standard datasets such as, HMDB, UCF-50, Olympic Sports and KTH.
237	Discriminative Brain Effective Connectivity Analysis for Alzheimer’s Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network	Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, Dinggang Shen	In this paper, we propose a learning-based approach that integrates the benefits of generative and discriminative methods to recover effective connectivity.
238	Robust Monocular Epipolar Flow Estimation	Koichiro Yamaguchi, David McAllester, Raquel Urtasun	We propose to take advantage of this fact and estimate flow along the epipolar lines of the egomotion.
239	Heterogeneous Visual Features Fusion via Sparse Multimodal Machine	Hua Wang, Feiping Nie, Heng Huang, Chris Ding	In this paper, We propose a novel Sparse Multimodal Learning (SMML) approach to integrate such heterogeneous features by using the joint structured sparsity regularizations to learn the feature importance of for the vision tasks from both group-wise and individual point of views.
240	A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching	Pradipto Das, Chenliang Xu, Richard F. Doell, Jason J. Corso	In this paper, we combine ideas from the bottom-up and top-down approaches to image description and propose a method for video description that captures the most relevant contents of a video in a natural language description.
241	Online Dominant and Anomalous Behavior Detection in Videos	Mehrsan Javan Roshtkhari, Martin D. Levine	We present a novel approach for video parsing and simultaneous online learning of dominant and anomalous behaviors in surveillance videos.
242	Learning Class-to-Image Distance with Object Matchings	Guang-Tong Zhou, Tian Lan, Weilong Yang, Greg Mori	We conduct image classification by learning a class-toimage distance function that matches objects.
243	Spectral Modeling and Relighting of Reflective-Fluorescent Scenes	Antony Lam, Imari Sato	In this paper, we describe the very different ways that reflectance and fluorescence interact with illuminants and show the need to explicitly consider fluorescence in the relighting problem.
244	Is There a Procedural Logic to Architecture?	Julien Weissenberg, Hayko Riemenschneider, Mukta Prasad, Luc Van Gool	We propose a novel procedural modelling method to automatically learn a grammar from a set of fac,ades, generate new fac,ade instances and compare fac,ades.
245	Motion Estimation for Self-Driving Cars with a Generalized Camera	Gim Hee Lee, Friedrich Faundorfer, Marc Pollefeys	In this paper, we present a visual ego-motion estimation algorithm for a self-driving car equipped with a closeto-market multi-camera system.
246	Histograms of Sparse Codes for Object Detection	Xiaofeng Ren, Deva Ramanan	We provide an affirmative answer by proposing and investigating a sparse representation for object detection, Histograms of Sparse Codes (HSC).
247	Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions	Dong Zhang, Omar Javed, Mubarak Shah	In this paper, we propose a novel approach to extract primary object segments in videos in the ‘object proposal’ domain.
248	Capturing Complex Spatio-temporal Relations among Facial Muscles for Facial Expression Recognition	Ziheng Wang, Shangfei Wang, Qiang Ji	To overcome these limitations and take full advantage of the spatio-temporal information, we propose to model the facial expression as a complex activity that consists of temporally overlapping or sequential primitive facial events.
249	Bayesian Depth-from-Defocus with Shading Constraints	Chen Li, Shuochen Su, Yasuyuki Matsushita, Kun Zhou, Stephen Lin	We present a method that enhances the performance of depth-from-defocus (DFD) through the use of shading information.
250	Sparse Output Coding for Large-Scale Visual Recognition	Bin Zhao, Eric P. Xing	In this paper, we propose sparse output coding, a principled way for large-scale multi-class classification, by turning high-cardinality multi-class categorization into a bit-by-bit decoding problem.
251	Boundary Cues for 3D Object Shape Recovery	Kevin Karsch, Zicheng Liao, Jason Rock, Jonathan T. Barron, Derek Hoiem	In this paper, we reconsider these perhaps overlooked “boundary” cues (such as self occlusions and folds in a surface), as well as many other established constraints for shape reconstruction.
252	Image Segmentation by Cascaded Region Agglomeration	Zhile Ren, Gregory Shakhnarovich	We propose a hierarchical segmentation algorithm that starts with a very fine oversegmentation and gradually merges regions using a cascade of boundary classifiers.
253	Spatial Inference Machines	Roman Shapovalov, Dmitry Vetrov, Pushmeet Kohli	This paper addresses the problem of semantic segmentation of 3D point clouds.
254	Can a Fully Unconstrained Imaging Model Be Applied Effectively to Central Cameras?	Filippo Bergamasco, Andrea Albarelli, Emanuele Rodola, Andrea Torsello	In this paper we propose the use of an unconstrained model even in standard central camera settings dominated by the pinhole model, and introduce a novel calibration approach that can deal effectively with the huge number of free parameters associated with it, resulting in a higher precision calibration than what is possible with the standard pinhole model with correction for radial distortion.
255	Learning Compact Binary Codes for Visual Tracking	Xi Li, Chunhua Shen, Anthony Dick, Anton van den Hengel	In this paper, we propose a visual tracker in which objects are represented by compact and discriminative binary codes.
256	Efficient Maximum Appearance Search for Large-Scale Object Detection	Qiang Chen, Zheng Song, Rogerio Feris, Ankur Datta, Liangliang Cao, Zhongyang Huang, Shuicheng Yan	In this paper, we present the Efficient Maximum Appearance Search (EMAS) model which is an order of magnitude faster than the existing state-of-the-art large-scale object detection approaches, while maintaining comparable accuracy.
257	A New Perspective on Uncalibrated Photometric Stereo	Thoma Papadhimitri, Paolo Favaro	We investigate the problem of reconstructing normals, albedo and lights of Lambertian surfaces in uncalibrated photometric stereo under the perspective projection model.
258	A Joint Model for 2D and 3D Pose Estimation from a Single Image	Edgar Simo-Serra, Ariadna Quattoni, Carme Torras, Francesc Moreno-Noguer	In this paper, we address this issue by jointly solving both the 2D detection and the 3D inference problems.
259	A Statistical Model for Recreational Trails in Aerial Images	Andrew Predoehl, Scott Morris, Kobus Barnard	We present a statistical model of aerial images of recreational trails, and a method to infer trail routes in such images.
260	Learning Video Saliency from Human Gaze Using Candidate Selection	Dmitry Rudoy, Dan B. Goldman, Eli Shechtman, Lihi Zelnik-Manor	In this paper we propose a novel method for video saliency estimation, which is inspired by the way people watch videos.
261	Designing Category-Level Attributes for Discriminative Visual Recognition	Felix X. Yu, Liangliang Cao, Rogerio S. Feris, John R. Smith, Shih-Fu Chang	In this paper, we propose a novel formulation to automatically design discriminative “category-level attributes”, which can be efficiently encoded by a compact category-attribute matrix.
262	Dense Segmentation-Aware Descriptors	Eduard Trulls, Iasonas Kokkinos, Alberto Sanfeliu, Francesc Moreno-Noguer	In this work we exploit segmentation to construct appearance descriptors that can robustly deal with occlusion and background changes.
263	Modeling Mutual Visibility Relationship in Pedestrian Detection	Wanli Ouyang, Xingyu Zeng, Xiaogang Wang	In this paper, we propose a mutual visibility deep model that jointly estimates the visibility statuses of overlapping pedestrians.
264	Discriminatively Trained And-Or Tree Models for Object Detection	Xi Song, Tianfu Wu, Yunde Jia, Song-Chun Zhu	This paper presents a method of learning reconfigurable And-Or Tree (AOT) models discriminatively from weakly annotated data for object detection.
265	Intrinsic Scene Properties from a Single RGB-D Image	Jonathan T. Barron, Jitendra Malik	In this paper we extend the “shape, illumination and reflectance from shading” (SIRFS) model [3, 4], which recovers intrinsic scene properties from a single image.
266	Cross-View Image Geolocalization	Tsung-Yi Lin, Serge Belongie, James Hays	In this paper, we introduce a cross-view feature translation approach to greatly extend the reach of image geolocalization methods.
267	Learning Cross-Domain Information Transfer for Location Recognition and Clustering	Raghuraman Gopalan	In contrast to many existing methods that primarily model discriminative information corresponding to different locations, we propose joint learning of information that images across locations share and vary upon.
268	Statistical Textural Distinctiveness for Salient Region Detection in Natural Images	Christian Scharfenberger, Alexander Wong, Khalil Fergani, John S. Zelek, David A. Clausi	A novel statistical textural distinctiveness approach for robustly detecting salient regions in natural images is proposed.
269	Robust Multi-resolution Pedestrian Detection in Traffic Scenes	Junjie Yan, Xucong Zhang, Zhen Lei, Shengcai Liao, Stan Z. Li	In this paper, we take pedestrian detection in different resolutions as different but related problems, and propose a Multi-Task model to jointly consider their commonness and differences.
270	Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking	Martin Hofmann, Daniel Wolf, Gerhard Rigoll	In this work, we present a combined maximum a posteriori (MAP) formulation, which jointly models multicamera reconstruction as well as global temporal data association.
271	Recognizing Activities via Bag of Words for Attribute Dynamics	Weixin Li, Qian Yu, Harpreet Sawhney, Nuno Vasconcelos	In this work, we propose a novel video representation for activity recognition that models video dynamics with attributes of activities.
272	Towards Fast and Accurate Segmentation	Camillo J. Taylor	In this paper we explore approaches to accelerating segmentation and edge detection algorithms based on the gPb framework.
273	Fast, Accurate Detection of 100,000 Object Classes on a Single Machine	Thomas Dean, Mark A. Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, Jay Yagnik	We exploit locality-sensitive hashing to replace the dot-product kernel operator in the convolution with a fixed number of hash-table probes that effectively sample all of the filter responses in time independent of the size of the filter bank.
274	Robust Object Co-detection	Xin Guo, Dong Liu, Brendan Jou, Mojun Zhu, Anni Cai, Shih-Fu Chang	In this paper, we propose a novel, robust approach to dramatically enhance co-detection by extracting a shared low-rank representation of the object instances in multiple feature spaces.
275	Supervised Kernel Descriptors for Visual Recognition	Peng Wang, Jingdong Wang, Gang Zeng, Weiwei Xu, Hongbin Zha, Shipeng Li	In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, which we call supervised kernel descriptors (SKDES).
276	Shape from Silhouette Probability Maps: Reconstruction of Thin Objects in the Presence of Silhouette Extraction and Calibration Error	Amy Tabb	Since the pseudo-Boolean minimization problem is NP-Hard for nonsubmodular functions, we developed an algorithm for an approximate solution using local minimum search.
277	Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation	Jordi Pont-Tuset, Ferran Marques	As a conclusion, this paper proposes the precision-recall curves for boundaries and for objects-and-parts as the tool of choice for the supervised evaluation of image segmentation. We make the datasets and code of all the measures publicly available.
278	A Fast Approximate AIB Algorithm for Distributional Word Clustering	Lei Wang, Jianjia Zhang, Luping Zhou, Wanqing Li	Based on this finding, we propose a fast approximate AIB algorithm and show that it can significantly improve the computational efficiency of AIB while well maintaining or even slightly increasing its classification performance.
279	Separable Dictionary Learning	Simon Hawe, Matthias Seibert, Martin Kleinsteuber	The approach presented in this paper aims at overcoming these drawbacks by allowing a separable structure on the dictionary throughout the learning process.
280	Representing and Discovering Adversarial Team Behaviors Using Player Roles	Patrick Lucey, Alina Bialkowski, Peter Carr, Stuart Morgan, Iain Matthews, Yaser Sheikh	In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain.
281	Object-Centric Anomaly Detection by Attribute-Based Reasoning	Babak Saleh, Ali Farhadi, Ahmed Elgammal	In this paper we introduce the abnormality detection as a recognition problem and show how to model typicalities and, consequently, meaningful deviations from prototypical properties of categories. We introduce the abnormality detection dataset and show interesting results on how to reason about abnormalities.
282	Cartesian K-Means	Mohammad Norouzi, David J. Fleet	We develop new models with a compositional parameterization of cluster centers, so representational capacity increases super-linearly in the number of parameters.
283	Optimal Geometric Fitting under the Truncated L2-Norm	Erik Ask, Olof Enqvist, Fredrik Kahl	We apply our framework to a series of hard registration and stitching problems demonstrating that the approach is not only of theoretical interest.
284	Pedestrian Detection with Unsupervised Multi-stage Feature Learning	Pierre Sermanet, Koray Kavukcuoglu, Soumith Chintala, Yann Lecun	Adding to the list of successful applications of deep learning methods to vision, we report state-of-theart and competitive results on all major pedestrian datasets with a convolutional network model.
285	Integrating Grammar and Segmentation for Human Pose Estimation	Brandon Rothrock, Seyoung Park, Song-Chun Zhu	In this paper we present a compositional and-or graph grammar model for human pose estimation.
286	Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images	Jamie Shotton, Ben Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, Andrew Fitzgibbon	We address the problem of inferring the pose of an RGB-D camera relative to a known 3D scene, given only a single acquired image.
287	Joint Detection, Tracking and Mapping by Semantic Bundle Adjustment	Nicola Fioraio, Luigi Di Stefano	In this paper we propose a novel Semantic Bundle Adjustment framework whereby known rigid stationary objects are detected while tracking the camera and mapping the environment.
288	Robust Region Grouping via Internal Patch Statistics	Xiaobai Liu, Liang Lin, Alan L. Yuille	In this work, we present an efficient multi-scale low-rank representation for image segmentation.
289	Boundary Detection Benchmarking: Beyond F-Measures	Xiaodi Hou, Alan Yuille, Christof Koch	The goal of this paper is to identify the potential pitfalls of today’s most popular boundary benchmark, BSDS 300.
290	Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes	Srikumar Ramalingam, Jaishanker K. Pillai, Arpit Jain, Yuichi Taguchi	In this paper, we consider the problem of detecting junctions and using them for recovering the spatial layout of an indoor scene.
291	What Makes a Patch Distinct?	Ran Margolin, Ayellet Tal, Lihi Zelnik-Manor	We propose a simple, yet powerful, algorithm that integrates these three factors.
292	Detection- and Trajectory-Level Exclusion in Multiple Object Tracking	Anton Milan, Konrad Schindler, Stefan Roth	We address this using a mixed discrete-continuous conditional random field (CRF) that explicitly models both types of constraints: Exclusion between conflicting observations with supermodular pairwise terms, and exclusion between trajectories by generalizing global label costs to suppress the co-occurrence of incompatible labels (trajectories).
293	Real-Time Model-Based Rigid Object Pose Estimation and Tracking Combining Dense and Sparse Visual Cues	Karl Pauwels, Leonardo Rubio, Javier Diaz, Eduardo Ros	We propose a novel model-based method for estimating and tracking the six-degrees-of-freedom (6DOF) pose of rigid objects of arbitrary shapes in real-time. Since a benchmark dataset that enables the evaluation of stereo-vision-based pose estimators in complex scenarios is currently missing in the literature, we have introduced a novel synthetic benchmark dataset with varying objects, background motion, noise and occlusions.
294	Unnatural L0 Sparse Representation for Natural Image Deblurring	Li Xu, Shicheng Zheng, Jiaya Jia	We show in this paper that the success of previous maximum a posterior (MAP) based blur removal methods partly stems from their respective intermediate steps, which implicitly or explicitly create an unnatural representation containing salient image structures.
295	Decoding Children’s Social Behavior	J. Rehg, G. Abowd, A. Rozga, M. Romero, M. Clements, S. Sclaroff, I. Essa, O. Ousley, Y. Li, C. Kim, H. Rao, J. Kim, L. Lo Presti, J. Zhang, D. Lantsman, J. Bidwell, Z. Ye	We identify the key technical challenges in analyzing these behaviors, and describe methods for decoding the interactions. We introduce a new problem domain for activity recognition: the analysis of children’s social and communicative behaviors based on video and audio data.
296	Finding Group Interactions in Social Clutter	Ruonan Li, Parker Porfilio, Todd Zickler	We consider the problem of finding distinctive social interactions involving groups of agents embedded in larger social gatherings.
297	Least Soft-Threshold Squares Tracking	Dong Wang, Huchuan Lu, Ming-Hsuan Yang	In this paper, we propose a generative tracking method based on a novel robust linear regression algorithm.
298	Online Robust Dictionary Learning	Cewu Lu, Jiaping Shi, Jiaya Jia	In this paper, we propose a new online framework enabling the use of ersparse data fitting term in robust dictionary learning, notably enhancing the usability and practicality of this important technique.
299	Learning the Change for Automatic Image Cropping	Jianzhou Yan, Stephen Lin, Sing Bing Kang, Xiaoou Tang	In this paper, we present an automatic cropping technique that accounts for the two primary considerations of people when they crop: removal of distracting content, and enhancement of overall composition.
300	Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems	Won Hwa Kim, Moo K. Chung, Vikas Singh	In this paper, we adapt recent results in harmonic analysis, to derive NonEuclidean Wavelets based algorithms for a range of shape analysis problems in vision and medical imaging.
301	Stochastic Deconvolution	James Gregson, Felix Heide, Matthias B. Hullin, Mushfiqur Rouf, Wolfgang Heidrich	We present a novel stochastic framework for non-blind deconvolution based on point samples obtained from random walks.
302	Nonparametric Scene Parsing with Adaptive Feature Relevance and Semantic Context	Gautam Singh, Jana Kosecka	This paper presents a nonparametric approach to semantic parsing using small patches and simple gradient, color and location features.
303	Social Role Discovery in Human Events	Vignesh Ramanathan, Bangpeng Yao, Li Fei-Fei	Since social roles are described by the interaction between people in an event, we propose a Conditional Random Field to model the inter-role interactions, along with person specific social descriptors.
304	Learning to Estimate and Remove Non-uniform Image Blur	Florent Couzinie-Devy, Jian Sun, Karteek Alahari, Jean Ponce	We present qualitative results on real images, and use synthetic data to quantitatively compare our approach to the publicly available implementation of Chakrabarti et al. [5].
305	Scene Parsing by Integrating Function, Geometry and Appearance Models	Yibiao Zhao, Song-Chun Zhu	In this paper, we present an algorithm to parse indoor images based on two observations: i) The functionality is the most essential property to define an indoor object, e.g. “a chair to sit on”; ii) The geometry (3D shape) of an object is designed to serve its function.
306	Efficient Detector Adaptation for Object Detection in a Video	Pramod Sharma, Ram Nevatia	In this work, we present a novel and efficient detector adaptation method which improves the performance of an offline trained classifier (baseline classifier) by adapting it to new test datasets.
307	Evaluation of Color STIPs for Human Action Recognition	Ivo Everts, Jan C. van Gemert, Theo Gevers	This paper is concerned with recognizing realistic human actions in videos based on spatio-temporal interest points (STIPs).
308	A Global Approach for the Detection of Vanishing Points and Mutually Orthogonal Vanishing Directions	Michel Antunes, Joao P. Barreto	This article presents a new global approach for detecting vanishing points and groups of mutually orthogonal vanishing directions using lines detected in images of man-made environments.
309	Poselet Conditioned Pictorial Structures	Leonid Pishchulin, Mykhaylo Andriluka, Peter Gehler, Bernt Schiele	In this paper we consider the challenging problem of articulated human pose estimation in still images.
310	Enriching Texture Analysis with Semantic Data	Tim Matthews, Mark S. Nixon, Mahesan Niranjan	We argue for the importance of explicit semantic modelling in human-centred texture analysis tasks such as retrieval, annotation, synthesis, and zero-shot learning.
311	Scene Text Recognition Using Part-Based Tree-Structured Character Detection	Cunzhao Shi, Chunheng Wang, Baihua Xiao, Yang Zhang, Song Gao, Zhong Zhang	In this paper, we propose a novel scene text recognition method using part-based tree-structured character detection.
312	MODEC: Multimodal Decomposable Models for Human Pose Estimation	Ben Sapp, Ben Taskar	We propose a multimodal, decomposable model for articulated human pose estimation in monocular images.
313	Multi-task Sparse Learning with Beta Process Prior for Action Recognition	Chunfeng Yuan, Weiming Hu, Guodong Tian, Shuang Yang, Haoran Wang	In this paper, we formulate human action recognition as a novel Multi-Task Sparse Learning(MTSL) framework which aims to construct a test sample with multiple features from as few bases as possible.
314	Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras	Donald G. Dansereau, Oscar Pizarro, Stefan B. Williams	We describe a decoding, calibration and rectification procedure for lenselet-based plenoptic cameras appropriate for a range of computer vision applications.
315	Hierarchical Video Representation with Trajectory Binary Partition Tree	Guillem Palou, Philippe Salembier	As early stage of video processing, we introduce an iterative trajectory merging algorithm that produces a regionbased and hierarchical representation of the video sequence, called the Trajectory Binary Partition Tree (BPT).
316	Cloud Motion as a Calibration Cue	Nathan Jacobs, Mohammad T. Islam, Scott Workman	This work introduces several new methods that use observations of an outdoor scene over days and weeks to estimate radial distortion, focal length and geo-orientation.
317	FasT-Match: Fast Affine Template Matching	Simon Korman, Daniel Reichman, Gilad Tsur, Shai Avidan	There is a huge number of transformations to consider but we prove that they can be sampled using a density that depends on the smoothness of the image.
318	Dense Non-rigid Point-Matching Using Random Projections	Raffay Hamid, Dennis Decoste, Chih-Jen Lin	We present a robust and efficient technique for matching dense sets of points undergoing non-rigid spatial transformations. To show the effectiveness of our approach, we present a systematic set of experiments and results for the problem of dense non-rigid image-feature matching.
319	Large Displacement Optical Flow from Nearest Neighbor Fields	Zhuoyuan Chen, Hailin Jin, Zhe Lin, Scott Cohen, Ying Wu	We present an optical flow algorithm for large displacement motions.
320	Hallucinated Humans as the Hidden Context for Labeling 3D Scenes	Yun Jiang, Hema Koppula, Ashutosh Saxena	In this paper, we hypothesize that such relationships are only an artifact of certain hidden factors, such as humans.
321	Discrete MRF Inference of Marginal Densities for Non-uniformly Discretized Variable Space	Masaki Saito, Takayuki Okatani, Koichiro Deguchi	In this paper, we show a novel formulation for this continuous-discrete conversion.
322	Efficient Large-Scale Structured Learning	Steve Branson, Oscar Beijbom, Serge Belongie	We introduce an algorithm, SVM-IS, for structured SVM learning that is computationally scalable to very large datasets and complex structural representations.
323	Relative Volume Constraints for Single View 3D Reconstruction	Eno Toppe, Claudia Nieuwenhuis, Daniel Cremers	We introduce the concept of relative volume constraints in order to account for insufficient information in the reconstruction of 3D objects from a single image.
324	Uncalibrated Photometric Stereo for Unknown Isotropic Reflectances	Feng Lu, Yasuyuki Matsushita, Imari Sato, Takahiro Okabe, Yoichi Sato	We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances.
325	Image Understanding from Experts’ Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes	Rui Li, Pengcheng Shi, Anne R. Haake	In this paper, we present a hierarchical probabilistic framework to summarize the stereotypical and idiosyncratic eye movement patterns shared within 11 board-certified dermatologists while they are examining and diagnosing medical images.
326	Robust Discriminative Response Map Fitting with Constrained Local Models	Akshay Asthana, Stefanos Zafeiriou, Shiyang Cheng, Maja Pantic	We present a novel discriminative regression based approach for the Constrained Local Models (CLMs) framework, referred to as the Discriminative Response Map Fitting (DRMF) method, which shows impressive performance in the generic face fitting scenario.
327	Unconstrained Monocular 3D Human Pose Estimation by Action Detection and Cross-Modality Regression Forest	Tsz-Ho Yu, Tae-Kyun Kim, Roberto Cipolla	We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video.
328	Revisiting Depth Layers from Occlusions	Adarsh Kowdle, Andrew Gallagher, Tsuhan Chen	In this work, we consider images of a scene with a moving object captured by a static camera.
329	Efficient Object Detection and Segmentation for Fine-Grained Recognition	Anelia Angelova, Shenghuo Zhu	We propose a detection and segmentation algorithm for the purposes of fine-grained recognition.
330	Fast Rigid Motion Segmentation via Incrementally-Complex Local Models	Fernando Flores-Mangas, Allan D. Jepson	This paper proposes a method that dramatically reduces this cost (by two or three orders of magnitude) with minimal accuracy loss (from 98.8% achieved by the state of the art, to 96.2% achieved by our method on the standard Hopkins 155 dataset).
331	A Lazy Man’s Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration	Peter Welinder, Max Welling, Pietro Perona	We study the case where data is plentiful, but labels are expensive.
332	Motionlets: Mid-level 3D Parts for Human Motion Recognition	LiMin Wang, Yu Qiao, Xiaoou Tang	This paper proposes motionlet, a mid-level and spatiotemporal part, for human motion recognition.
333	Understanding Indoor Scenes Using 3D Geometric Phrases	Wongun Choi, Yu-Wei Chao, Caroline Pantofaru, Silvio Savarese	We present a hierarchical scene model for learning and reasoning about complex indoor scenes which is computationally tractable, can be learned from a reasonable amount of training data, and avoids oversimplification.
334	Intrinsic Characterization of Dynamic Surfaces	Tony Tung, Takashi Matsuyama	This paper presents a novel approach to characterize deformable surface using intrinsic property dynamics.
335	Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-Mounted Camera	Ken Sakurada, Takayuki Okatani, Koichiro Deguchi	This paper proposes a method for detecting temporal changes of the three-dimensional structure of an outdoor scene from its multi-view images captured at two separate times.
336	Part-Based Visual Tracking with Online Latent Structural Learning	Rui Yao, Qinfeng Shi, Chunhua Shen, Yanning Zhang, Anton van den Hengel	We thus propose a method which models the unknown parts using latent variables.
337	A Higher-Order CRF Model for Road Network Extraction	Jan D. Wegner, Javier A. Montoya-Zegarra, Konrad Schindler	The aim of this work is to extract the road network from aerial images.
338	Fully-Connected CRFs with Non-Parametric Pairwise Potential	Neill D.F. Campbell, Kartic Subr, Jan Kautz	To this end, we propose a density estimation technique to derive conditional pairwise potentials in a nonparametric manner.
339	Hierarchical Saliency Detection	Qiong Yan, Li Xu, Jianping Shi, Jiaya Jia	We tackle it from a scale point of view and propose a multi-layer approach to analyze saliency cues.
340	Depth Acquisition from Density Modulated Binary Patterns	Zhe Yang, Zhiwei Xiong, Yueyi Zhang, Jiao Wang, Feng Wu	This paper proposes novel density modulated binary patterns for depth acquisition.
341	Pose from Flow and Flow from Pose	Katerina Fragkiadaki, Han Hu, Jianbo Shi	We build a segmentation-detection algorithm that mediates the information between body parts recognition, and multi-frame motion grouping to improve both pose detection and tracking.
342	Composite Statistical Inference for Semantic Segmentation	Fuxin Li, Joao Carreira, Guy Lebanon, Cristian Sminchisescu	In this paper we present an inference procedure for the semantic segmentation of images.
343	The Variational Structure of Disparity and Regularization of 4D Light Fields	Bastian Goldluecke, Sven Wanner	In this work, we analyze regularization of light fields in variational frameworks and show that their variational structure is induced by disparity, which is in this context best understood as a vector field on epipolar plane image space.
344	Gauging Association Patterns of Chromosome Territories via Chromatic Median	Hu Ding, Branislav Stojkovic, Ronald Berezney, Jinhui Xu	In this paper, we introduce a novel algorithmic tool for investigating association patterns of chromosome territories in a population of cells.
345	Detecting Pulse from Head Motions in Video	Guha Balakrishnan, Fredo Durand, John Guttag	Our method tracks features on the head and performs principal component analysis (PCA) to decompose their trajectories into a set of component motions.
346	Articulated Pose Estimation Using Discriminative Armlet Classifiers	Georgia Gkioxari, Pablo Arbelaez, Lubomir Bourdev, Jitendra Malik	We propose a novel approach for human pose estimation in real-world cluttered scenes, and focus on the challenging problem of predicting the pose of both arms for each person in the image.
347	Salient Object Detection: A Discriminative Regional Feature Integration Approach	Huaizu Jiang, Jingdong Wang, Zejian Yuan, Yang Wu, Nanning Zheng, Shipeng Li	In this paper, we regard saliency map computation as a regression problem.
348	Learning Locally-Adaptive Decision Functions for Person Verification	Zhen Li, Shiyu Chang, Feng Liang, Thomas S. Huang, Liangliang Cao, John R. Smith	This paper proposes to learn a decision function for verification that can be viewed as a joint model of a distance metric and a locally adaptive thresholding rule.
349	BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition	Jiri Filip, Radomir Vavra, Michal Haindl, Pavel Zid, Mikulas Krupika, Vlastimil Havran	In this paper we introduce unique publicly available dense anisotropic BRDF data measurements.
350	Explicit Occlusion Modeling for 3D Object Class Representations	M. Zeeshan Zia, Michael Stark, Konrad Schindler	In this paper, we tackle the challenge of modeling occlusion in the context of a 3D geometric object class model that is capable of fine-grained, part-level 3D object reconstruction.
351	Tag Taxonomy Aware Dictionary Learning for Region Tagging	Jingjing Zheng, Zhuolin Jiang	In this paper, using the given tag taxonomy, we propose to jointly learn multi-layer hierarchical dictionaries and corresponding linear classifiers for region tagging.
352	A Fast Semidefinite Approach to Solving Binary Quadratic Problems	Peng Wang, Chunhua Shen, Anton van den Hengel	We present a new SDP formulation for BQPs, with two desirable properties.
353	Learning without Human Scores for Blind Image Quality Assessment	Wufeng Xue, Lei Zhang, Xuanqin Mou	This paper makes a good effort to answer this question.
354	Hollywood 3D: Recognizing Actions in 3D Natural Scenes	Simon Hadfield, Richard Bowden	This paper presents a new dataset, for benchmarking action recognition algorithms in natural environments, while making use of 3D information. We make the dataset including stereo video, estimated depth maps and all code required to reproduce the benchmark results, available to the wider community.
355	3D Pictorial Structures for Multiple View Articulated Pose Estimation	Magnus Burenius, Josephine Sullivan, Stefan Carlsson	We consider the problem of automatically estimating the 3D pose of humans from images, taken from multiple calibrated views.
356	Improving the Visual Comprehension of Point Sets	Sagi Katz, Ayellet Tal	Our goal is to reduce the number of points in a point set, for improving the visual comprehension from a given viewpoint. In addition, we introduce a new dual problem, for determining visibility of a point from infinity, and show how a limitation of its solution can be leveraged in a similar way.
357	Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices	Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Harandi	In this paper, inspired by kernel methods, we propose to map SPD matrices to a high dimensional Hilbert space where Euclidean geometry applies.
358	Graph Transduction Learning with Connectivity Constraints with Application to Multiple Foreground Cosegmentation	Tianyang Ma, Longin Jan Latecki	Based on this fact, we design a cutting-plane algorithm to solve the integrated problem.
359	A Max-Margin Riffled Independence Model for Image Tag Ranking	Tian Lan, Greg Mori	We propose Max-Margin Riffled Independence Model (MMRIM), a new method for image tag ranking modeling the structured preferences among tags.
360	Label Propagation from ImageNet to 3D Point Clouds	Yan Wang, Rongrong Ji, Shih-Fu Chang	In this paper, we overcome this challenge by utilizing the existing massive 2D semantic labeled datasets from decadelong community efforts, such as ImageNet and LabelMe, and a novel “cross-domain” label propagation approach.
361	Supervised Semantic Gradient Extraction Using Linear-Time Optimization	Shulin Yang, Jue Wang, Linda Shapiro	This paper proposes a new supervised semantic edge and gradient extraction approach, which allows the user to roughly scribble over the desired region to extract semantically-dominant and coherent edges in it.
362	Deep Learning Shape Priors for Object Segmentation	Fei Chen, Huimin Yu, Roland Hu, Xunxun Zeng	In this paper we introduce a new shape-driven approach for object segmentation.
363	Consensus of k-NNs for Robust Neighborhood Selection on Graph-Based Manifolds	Vittal Premachandran, Ramakrishna Kakarala	In this paper, we propose a way to select a robust neighborhood using the consensus of multiple rounds of k-NNs.
364	Semi-supervised Learning with Constraints for Person Identification in Multimedia Data	Martin Bauml, Makarand Tapaswi, Rainer Stiefelhagen	We propose a unified learning framework for multiclass classification which incorporates labeled and unlabeled data, and constraints between pairs of features in the training.
365	Capturing Layers in Image Collections with Componential Models: From the Layered Epitome to the Componential Counting Grid	Alessandro Perina, Nebojsa Jojic	In this paper we introduce a family of componential models, dubbed the Componential Counting Grid, whose members represent each input image by multiple latent locations, rather than just one.
366	Layer Depth Denoising and Completion for Structured-Light RGB-D Cameras	Ju Shen, Sen-Ching S. Cheung	In this paper, we propose a novel probabilistic model to capture various types of uncertainties in the depth measurement process among structured-light systems.
367	Adaptive Compressed Tomography Sensing	Oren Barkan, Jonathan Weill, Amir Averbuch, Shai Dekel	We propose a mathematical model for adaptive CT acquisition whose goal is to reduce dosage levels while maintaining high image quality at the same time.
368	Detection of Manipulation Action Consequences (MAC)	Yezhou Yang, Cornelia Fermuller, Yiannis Aloimonos	In this paper a technique is developed to recognize these action consequences. We provide a new dataset, called Manipulation Action Consequences (MAC 1.0), which can serve as testbed for other studies on this topic.
369	Efficient Color Boundary Detection with Color-Opponent Mechanisms	Kaifu Yang, Shaobing Gao, Chaoyi Li, Yongjie Li	In this study, we propose a new framework for boundary detection in complex natural scenes based on the color-opponent mechanisms of the visual system.
370	Better Exploiting Motion for Better Action Recognition	Mihir Jain, Herve Jegou, Patrick Bouthemy	Our three contributions are complementary and lead to outperform all reported results by a significant margin on three challenging datasets, namely Hollywood 2, HMDB51 and Olympic Sports.
371	Constraints as Features	Shmuel Asafi, Daniel Cohen-Or	In this paper, we introduce a new approach to constrained clustering which treats the constraints as features.
372	Graph-Laplacian PCA: Closed-Form Solution and Robustness	Bo Jiang, Chris Ding, Bio Luo, Jin Tang	We propose a graph-Laplacian PCA (gLPCA) to learn a low dimensional representation of X that incorporates graph structures encoded in W .
373	Determining Motion Directly from Normal Flows Upon the Use of a Spherical Eye Platform	Tak-Wai Hui, Ronald Chung	We address the problem of recovering camera motion from video data, which does not require the establishment of feature correspondences or computation of optical flows but from normal flows directly.
374	Visual Place Recognition with Repetitive Structures	Akihiko Torii, Josef Sivic, Tomas Pajdla, Masatoshi Okutomi	In this work we show that repeated structures are not a nuisance but, when appropriately represented, they form an important distinguishing feature for many places.
375	Single-Pedestrian Detection Aided by Multi-pedestrian Detection	Wanli Ouyang, Xiaogang Wang	In this paper, we address the challenging problem of detecting pedestrians who appear in groups and have interaction.
376	Understanding Bayesian Rooms Using Composite 3D Object Models	Luca Del Pero, Joshua Bowdish, Bonnie Kermgard, Emily Hartley, Kobus Barnard	We develop a comprehensive Bayesian generative model for understanding indoor scenes.
377	Groupwise Registration via Graph Shrinkage on the Image Manifold	Shihui Ying, Guorong Wu, Qian Wang, Dinggang Shen	To solve this issue, we propose a novel groupwise registration algorithm for large population dataset, guided by the image distribution on the manifold.
378	On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit	Stefan Harmeling, Michael Hirsch, Bernhard Scholkopf	We establish a link between Fourier optics and a recent construction from the machine learning community termed the kernel mean map.
379	Background Modeling Based on Bidirectional Analysis	Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi	In this paper, we propose a new framework that leverages information from a future period.
380	Minimum Uncertainty Gap for Robust Visual Tracking	Junseok Kwon, Kyoung Mu Lee	We propose a novel tracking algorithm that robustly tracks the target by finding the state which minimizes uncertainty of the likelihood at current state.
381	Real-Time No-Reference Image Quality Assessment Based on Filter Learning	Peng Ye, Jayant Kumar, Le Kang, David Doermann	The contributions of our work are two-fold: first, the proposed method is highly efficient.
382	City-Scale Change Detection in Cadastral 3D Models Using Images	Aparna Taneja, Luca Ballan, Marc Pollefeys	In this paper, we propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city.
383	Occlusion Patterns for Object Class Detection	Bojan Pepikj, Michael Stark, Peter Gehler, Bernt Schiele	In this paper we leave the beaten path of methods that treat occlusion as just another source of noise instead, we include the occluder itself into the modelling, by mining distinctive, reoccurring occlusion patterns from annotated training data.
384	Local Fisher Discriminant Analysis for Pedestrian Re-identification	Sateesh Pedagadi, James Orwell, Sergio Velastin, Boghos Boghossian	This paper presents a novel approach to the pedestrian re-identification problem that uses metric learning to improve the state-of-the-art performance on standard public datasets.
385	Semi-supervised Node Splitting for Random Forest Construction	Xiao Liu, Mingli Song, Dacheng Tao, Zicheng Liu, Luming Zhang, Chun Chen, Jiajun Bu	In this paper, we present semi-supervised splitting to overcome this limitation by splitting nodes with the guidance of both labeled and unlabeled data.
386	Vantage Feature Frames for Fine-Grained Categorization	Asma Rejeb Sfar, Nozha Boujemaa, Donald Geman	We study fine-grained categorization, the task of distinguishing among (sub)categories of the same generic object class (e.g., birds), focusing on determining botanical species (leaves and orchids) from scanned images.
387	A Video Representation Using Temporal Superpixels	Jason Chang, Donglai Wei, John W. Fisher III	We develop a generative probabilistic model for temporally consistent superpixels in video sequences.
388	Structure Preserving Object Tracking	Lu Zhang, Laurens van der Maaten	In this paper, we propose a new multi-object model-free tracker (based on tracking-by-detection) that resolves this problem by incorporating spatial constraints between the objects.
389	Unsupervised Salience Learning for Person Re-identification	Rui Zhao, Wanli Ouyang, Xiaogang Wang	In this paper, we propose a novel perspective for person re-identification based on unsupervised salience learning.
390	Spatiotemporal Deformable Part Models for Action Detection	Yicong Tian, Rahul Sukthankar, Mubarak Shah	Deformable part models have achieved impressive performance for object detection, even on difficult image datasets.
391	Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics	Bo Zheng, Yibiao Zhao, Joey C. Yu, Katsushi Ikeuchi, Song-Chun Zhu	In this paper, we present an approach for scene understanding by reasoning physical stability of objects from point cloud.
392	Recovering Stereo Pairs from Anaglyphs	Armand Joulin, Sing Bing Kang	We propose a technique to reconstruct the original color stereo pair given such an anaglyph.
393	Axially Symmetric 3D Pots Configuration System Using Axis of Symmetry and Break Curve	Kilho Son, Eduardo B. Almeida, David B. Cooper	This paper introduces a novel approach for reassembling pot sherds found at archaeological excavation sites, for the purpose of reconstructing clay pots that had been made on a wheel.
394	Learning a Manifold as an Atlas	Nikolaos Pitelis, Chris Russell, Lourdes Agapito	In this work, we return to the underlying mathematical definition of a manifold and directly characterise learning a manifold as finding an atlas, or a set of overlapping charts, that accurately describe local structure.
395	Label-Embedding for Attribute-Based Classification	Zeynep Akata, Florent Perronnin, Zaid Harchaoui, Cordelia Schmid	We propose to view attribute-based image classification as a label-embedding problem: each class is embedded in the space of attribute vectors.
396	Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis	Christian Theriault, Nicolas Thome, Matthieu Cord	In this paper, we address the challenging problem of categorizing video sequences composed of dynamic natural scenes.
397	The Episolar Constraint: Monocular Shape from Shadow Correspondence	Austin Abrams, Kylia Miskell, Robert Pless	We demonstrate results across a variety of time-lapse sequences from webcams “in the wild.”
398	Learning and Calibrating Per-Location Classifiers for Visual Place Recognition	Petr Gronat, Guillaume Obozinski, Josef Sivic, Tomas Pajdla	The aim of this work is to localize a query photograph by finding other images depicting the same place in a large geotagged image database.
399	Blind Deconvolution of Widefield Fluorescence Microscopic Data by Regularization of the Optical Transfer Function (OTF)	Margret Keuper, Thorsten Schmidt, Maja Temerinac-Ott, Jan Padeken, Patrick Heun, Olaf Ronneberger, Thomas Brox	In this paper, we present a blind deconvolution method that improves results of state-of-theart deconvolution methods on widefield data by exploiting the properties of the widefield OTF.
400	Tensor-Based Human Body Modeling	Yinpeng Chen, Zicheng Liu, Zhengyou Zhang	In this paper, we present a novel approach to model 3D human body with variations on both human shape and pose, by exploring a tensor decomposition technique.
401	Segment-Tree Based Cost Aggregation for Stereo Matching	Xing Mei, Xun Sun, Weiming Dong, Haitao Wang, Xiaopeng Zhang	This paper presents a novel tree-based cost aggregation method for dense stereo matching.
402	Category Modeling from Just a Single Labeling: Use Depth Information to Guide the Learning of 2D Models	Quanshi Zhang, Xuan Song, Xiaowei Shao, Ryosuke Shibasaki, Huijing Zhao	We design a graphical model that uses object edges to represent object structures, and this paper aims to incrementally learn this category model from one labeled object and a number of casually captured scenes.
403	Human Pose Estimation Using a Joint Pixel-wise and Part-wise Formulation	Lubor Ladicky, Philip H.S. Torr, Andrew Zisserman	Our goal is to detect humans and estimate their 2D pose in single images.
404	Learning Separable Filters	Roberto Rigamonti, Amos Sironi, Vincent Lepetit, Pascal Fua	In this paper, we show that such filters can be computed as linear combinations of a smaller number of separable ones, thus greatly reducing the computational complexity at no cost in terms of performance.
405	Tracking Human Pose by Tracking Symmetric Parts	Varun Ramakrishna, Takeo Kanade, Yaser Sheikh	In this work, we present an occlusion aware algorithm for tracking human pose in an image sequence, that addresses the problem of double counting.
406	Facial Feature Tracking Under Varying Facial Expressions and Face Poses Based on Restricted Boltzmann Machines	Yue Wu, Zuoguan Wang, Qiang Ji	In this paper, we address this problem by proposing a face shape prior model that is constructed based on the Restricted Boltzmann Machines (RBM) and their variants.
407	Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines	Roni Mittelman, Honglak Lee, Benjamin Kuipers, Silvio Savarese	In order to address this issue, we propose a weakly supervised approach to learn mid-level features, where only class-level supervision is provided during training.
408	K-Means Hashing: An Affinity-Preserving Quantization Method for Learning Binary Compact Codes	Kaiming He, Fang Wen, Jian Sun	In this paper, we present a hashing method adopting the k-means quantization.
409	Rolling Riemannian Manifolds to Solve the Multi-class Classification Problem	Rui Caseiro, Pedro Martins, Joao F. Henriques, Fatima Silva Leite, Jorge Batista	A popular framework, valid over any Riemannian manifold, was proposed in [31] for binary classification.
410	Mesh Based Semantic Modelling for Indoor and Outdoor Scenes	Julien P.C. Valentin, Sunando Sengupta, Jonathan Warrell, Ali Shahrokni, Philip H.S. Torr	In this work we propose a principled way to generate object labelling in 3D.
411	A Bayesian Approach to Multimodal Visual Dictionary Learning	Go Irie, Dong Liu, Zhenguo Li, Shih-Fu Chang	We propose a novel Bayesian co-clustering model to jointly estimate the underlying distributions of the continuous image descriptors as well as the relationship between such distributions and the textual words through a unified Bayesian inference.
412	Photometric Ambient Occlusion	Daniel Hauagge, Scott Wehrwein, Kavita Bala, Noah Snavely	We present a method for computing ambient occlusion (AO) for a stack of images of a scene from a fixed viewpoint.
413	Beyond Physical Connections: Tree Models in Human Pose Estimation	Fang Wang, Yi Li	This paper attempts to address three questions: 1) are simple tree models sufficient?
414	Patch Match Filter: Efficient Edge-Aware Filtering Meets Randomized Search for Fast Correspondence Field Estimation	Jiangbo Lu, Hongsheng Yang, Dongbo Min, Minh N. Do	This paper presents a generic and fast computational framework for general multi-labeling problems called PatchMatch Filter (PMF).
415	Generalized Domain-Adaptive Dictionaries	Sumit Shekhar, Vishal M. Patel, Hien V. Nguyen, Rama Chellappa	In this paper, we investigate if it is possible to optimally represent both source and target by a common dictionary.
416	Supervised Descent Method and Its Applications to Face Alignment	Xuehan Xiong, Fernando De la Torre	To address these issues, this paper proposes a Supervised Descent Method (SDM) for minimizing a Non-linear Least Squares (NLS) function.
417	Self-Paced Learning for Long-Term Tracking	James S. Supancic III, Deva Ramanan	We describe both an offline algorithm (that processes frames in batch) and a linear-time online (i.e. causal) algorithm that approaches real-time performance.
418	A Machine Learning Approach for Non-blind Image Deconvolution	Christian J. Schuler, Harold Christopher Burger, Stefan Harmeling, Bernhard Scholkopf	In this work, we deal with space-invariant nonblind deconvolution.
419	Correlation Filters for Object Alignment	Vishnu Naresh Boddeti, Takeo Kanade, B.V.K. Vijaya Kumar	In this paper we present an efficient and robust landmark detection model which is designed specifically to minimize localization errors thereby leading to state-of-the-art object alignment performance.
420	Voxel Cloud Connectivity Segmentation – Supervoxels for Point Clouds	Jeremie Papon, Alexey Abramov, Markus Schoeler, Florentin Worgotter	We propose a novel over-segmentation algorithm which uses voxel relationships to produce over-segmentations which are fully consistent with the spatial geometry of the scene in three dimensional, rather than projective, space.
421	Adherent Raindrop Detection and Removal in Video	Shaodi You, Robby T. Tan, Rei Kawakami, Katsushi Ikeuchi	In this paper, a method that automatically detects and removes adherent raindrops is introduced.
422	Recovering Line-Networks in Images by Junction-Point Processes	Dengfeng Chai, Wolfgang Forstner, Florent Lafarge	We present an original method which provides structurally-coherent solutions.
423	Continuous Inference in Graphical Models with Polynomial Energies	Mathieu Salzmann	In this paper, we tackle the problem of performing inference in graphical models whose energy is a polynomial function of continuous variables.
424	Attribute-Based Detection of Unfamiliar Classes with Humans in the Loop	Catherine Wah, Serge Belongie	In this work, we propose a novel approach to the unfamiliar class detection task that builds on attribute-based classification methods, and we empirically demonstrate how classification accuracy is impacted by attribute noise and dataset “difficulty,” as quantified by the separation of classes in the attribute space.
425	Locally Aligned Feature Transforms across Views	Wei Li, Xiaogang Wang	In this paper, we propose a new approach for matching images observed in different camera views with complex cross-view transforms and apply it to person reidentification.
426	Sensing and Recognizing Surface Textures Using a GelSight Sensor	Rui Li, Edward H. Adelson	We built a database with 40 classes of taaactile textures using materials such as fabric, wood, and sannndpaper.
427	Universality of the Local Marginal Polytope	Daniel Prusa, Tomas Werner	We show that solving the LP relaxation of the MAP inference problem in graphical models (also known as the minsum problem, energy minimization, or weighted constraint satisfaction) is not easier than solving any LP.
428	Graph Matching with Anchor Nodes: A Learning Approach	Nan Hu, Raif M. Rustamov, Leonidas Guibas	In this paper, we consider the weighted graph matching problem with partially disclosed correspondences between a number of anchor nodes.
429	Blocks That Shout: Distinctive Parts for Scene Classification	Mayank Juneja, Andrea Vedaldi, C.V. Jawahar, Andrew Zisserman	In this paper, we propose a simple, efficient, and effective method to do so.
430	Megastereo: Constructing High-Resolution Stereo Panoramas	Christian Richardt, Yael Pritch, Henning Zimmer, Alexander Sorkine-Hornung	We present a solution for generating high-quality stereo panoramas at megapixel resolutions.
431	Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and Structural Information for Activity Recognition	Vinay Bettadapura, Grant Schindler, Thomas Ploetz, Irfan Essa	We present data-driven techniques to augment Bag of Words (BoW) models, which allow for more robust modeling and recognition of complex long-term activities, especially when the structure and topology of the activities are not known a priori.
432	Dense 3D Reconstruction from Severely Blurred Images Using a Single Moving Camera	Hee Seok Lee, Kuoung Mu Lee	To handle motion blur caused by rapid camera shakes, we propose a blur-aware depth reconstruction method, which utilizes a pixel correspondence that is obtained by considering the effect of motion blur.
433	A Practical Rank-Constrained Eight-Point Algorithm for Fundamental Matrix Estimation	Yinqiang Zheng, Shigeki Sugimoto, Masatoshi Okutomi	In this work, we present a new rank-2 constrained eight-point algorithm, which directly incorporates the rank-2 constraint in the minimization process.
434	Accurate Localization of 3D Objects from RGB-D Data Using Segmentation Hypotheses	Byung-soo Kim, Shili Xu, Silvio Savarese	In this paper we focus on the problem of detecting objects in 3D from RGB-D images.
435	Pixel-Level Hand Detection in Ego-centric Videos	Cheng Li, Kris M. Kitani	To quantify the challenges and performance in this new domain, we present a fully labeled indoor/outdoor ego-centric hand detection benchmark dataset containing over 200 million labeled pixels, which contains hand images taken under various illumination conditions.
436	Geometric Context from Videos	S. Hussain Raza, Matthias Grundmann, Irfan Essa	We present a novel algorithm for estimating the broad 3D geometric structure of outdoor video scenes. We built a novel, extensive dataset on geometric context of video to evaluate our method, consisting of over 100 groundtruth annotated outdoor videos with over 20,000 frames.
437	Exploiting the Power of Stereo Confidences	David Pfeiffer, Stefan Gehrig, Nicolai Schneider	In this paper, we make full use of the stereo confidence cues by propagating all confidence values along with the measured disparities in a Bayesian manner.
438	Optimizing 1-Nearest Prototype Classifiers	Paul Wohlhart, Martin Kostinger, Michael Donoser, Peter M. Roth, Horst Bischof	In this paper, we go a step beyond these approaches and purely focus on 1-nearest prototype classification, where we propose a novel algorithm for deriving optimal prototypes in a discriminative manner from the training samples.
439	Efficient 3D Endfiring TRUS Prostate Segmentation with Globally Optimized Rotational Symmetry	Jing Yuan, Wu Qiu, Eranga Ukwatta, Martin Rajchl, Xue-Cheng Tai, Aaron Fenster	In this work, we propose a novel global optimization approach to delineate 3D prostate boundaries using its rotational resliced images around a specified axis, which properly enforces the inherent rotational symmetry of prostate shapes to jointly adjust a series of 2D slicewise segmentations in the global 3D sense.
440	Robust Canonical Time Warping for the Alignment of Grossly Corrupted Sequences	Yannis Panagakis, Mihalis A. Nicolaou, Stefanos Zafeiriou, Maja Pantic	In this paper, building on recent advances on rank minimization and compressive sensing, a novel, robust to gross errors temporal alignment method is proposed.
441	The Generalized Laplacian Distance and Its Applications for Visual Matching	Elhanan Elboer, Michael Werman, Yacov Hel-Or	In this paper we explore the Laplacian distance, a distance function related to the graph Laplacian, and use it for visual search.
442	A Sentence Is Worth a Thousand Pixels	Sanja Fidler, Abhishek Sharma, Raquel Urtasun	We propose a holistic conditional random field model for semantic parsing which reasons jointly about which objects are present in the scene, their spatial extent as well as semantic segmentation, and employs text as well as image information as input.
443	Deep Convolutional Network Cascade for Facial Point Detection	Yi Sun, Xiaogang Wang, Xiaoou Tang	We propose a new approach for estimation of the positions of facial keypoints with three-level carefully designed convolutional networks.
444	Scalable Sparse Subspace Clustering	Xi Peng, Lei Zhang, Zhang Yi	In this paper, we address two problems in Sparse Subspace Clustering algorithm (SSC), i.e., scalability issue and out-of-sample problem.
445	Nonlinearly Constrained MRFs: Exploring the Intrinsic Dimensions of Higher-Order Cliques	Yun Zeng, Chaohui Wang, Stefano Soatto, Shing-Tung Yau	This paper introduces an efficient approach to integrating non-local statistics into the higher-order Markov Random Fields (MRFs) framework.
446	Seeking the Strongest Rigid Detector	Rodrigo Benenson, Markus Mathias, Tinne Tuytelaars, Luc Van Gool	In this paper we revisit some of the core assumptions in HOG+SVM and show that by properly designing the feature pooling, feature selection, preprocessing, and training methods, it is possible to reach top quality, at least for pedestrian detections, using a single rigid component.
447	An Approach to Pose-Based Action Recognition	Chunyu Wang, Yizhou Wang, Alan L. Yuille	More precisely, we obtain the K-best estimations output by the existing method and incorporate additional segmentation cues and temporal constraints to select the “best” one.
448	Pattern-Driven Colorization of 3D Surfaces	George Leifman, Ayellet Tal	We focus on surfaces with patterns and propose a novel algorithm for adding colors to these surfaces.
449	Dense Reconstruction Using 3D Object Shape Priors	Amaury Dame, Victor A. Prisacariu, Carl Y. Ren, Ian Reid	In this work we link dense SLAM to 3D object pose and shape recovery.
450	Modeling Actions through State Changes	Alireza Fathi, James M. Rehg	In this paper we present a model of action based on the change in the state of the environment.
451	GRASP Recurring Patterns from a Single View	Jingchen Liu, Yanxi Liu	We propose a novel unsupervised method for discovering recurring patterns from a single view.
452	Texture Enhanced Image Denoising via Gradient Histogram Preservation	Wangmeng Zuo, Lei Zhang, Chunwei Song, David Zhang	To address this problem, in this paper we propose a texture enhanced image denoising (TEID) method by enforcing the gradient distribution of the denoised image to be close to the estimated gradient distribution of the original image.
453	Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs	Roozbeh Mottaghi, Sanja Fidler, Jian Yao, Raquel Urtasun, Devi Parikh	In this work, we are interested in understanding the roles of these different tasks in aiding semantic segmentation.
454	Multi-source Multi-scale Counting in Extremely Dense Crowd Images	Haroon Idrees, Imran Saleemi, Cody Seibert, Mubarak Shah	We propose to leverage multiple sources of information to compute an estimate of the number of individuals present in an extremely dense crowd visible in a single image.
455	Non-uniform Motion Deblurring for Bilayer Scenes	Chandramouli Paramanand, Ambasamudram N. Rajagopalan	We address the problem of estimating the latent image of a static bilayer scene (consisting of a foreground and a background at different depths) from motion blurred observations captured with a handheld camera.
456	Specular Reflection Separation Using Dark Channel Prior	Hyeongwoo Kim, Hailin Jin, Sunil Hadap, Inso Kweon	We present a novel method to separate specular reflection from a single image.
457	Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification	Dong Chen, Xudong Cao, Fang Wen, Jian Sun	In this paper, we study the performance of a highdimensional feature.
458	Robust Estimation of Nonrigid Transformation for Point Set Registration	Jiayi Ma, Ji Zhao, Jinwen Tian, Zhuowen Tu, Alan L. Yuille	We present a new point matching algorithm for robust nonrigid registration.
459	Representing Videos Using Mid-level Discriminative Patches	Arpit Jain, Abhinav Gupta, Mikel Rodriguez, Larry S. Davis	We automatically mine these patches from hundreds of training videos and experimentally demonstrate that these patches establish correspondence across videos and align the videos for label transfer techniques.
460	Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild	Zhen Cui, Wen Li, Dong Xu, Shiguang Shan, Xilin Chen	To address this issue, we propose a new approach to extract robust face region descriptors.
461	Discriminative Sub-categorization	Minh Hoai, Andrew Zisserman	The objective of this work is to learn sub-categories.
462	Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images	Saurabh Gupta, Pablo Arbelaez, Jitendra Malik	We propose algorithms for object boundary detection and hierarchical segmentation that generalize the gP b ucm approach of [2] by making effective use of depth information.
463	Harvesting Mid-level Visual Concepts from Large-Scale Internet Images	Quannan Li, Jiajun Wu, Zhuowen Tu	In this paper, we propose a fully automatic algorithm which harvests visual concepts from a large number of Internet images (more than a quarter of a million) using text-based queries.
464	Sample-Specific Late Fusion for Visual Category Recognition	Dong Liu, Kuan-Ting Lai, Guangnan Ye, Ming-Syan Chen, Shih-Fu Chang	In this paper, we propose a sample-specific late fusion method to address this issue.
465	PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors	Keyang Shi, Keze Wang, Jiangbo Lu, Liang Lin	Motivated by these, we propose a generic and fast computational framework called PISA Pixelwise Image Saliency Aggregating complementary saliency cues based on color and structure contrasts with spatial priors holistically.
466	Simultaneous Super-Resolution of Depth and Images Using a Single Camera	Hee Seok Lee, Kuoung Mu Lee	In this paper, we propose a convex optimization framework for simultaneous estimation of super-resolved depth map and images from a single moving camera.
467	Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning	Tao Wang, Xuming He, Nick Barnes	We propose a structured Hough voting method for detecting objects with heavy occlusion in indoor environments.
468	3D-Based Reasoning with Blocks, Support, and Stability	Zhaoyin Jia, Andrew Gallagher, Ashutosh Saxena, Tsuhan Chen	We propose a new approach for parsing RGB-D images using 3D block units for volumetric reasoning.
469	Sampling Strategies for Real-Time Action Recognition	Feng Shi, Emil Petriu, Robert Laganiere	In this paper, we explore sampling with high density on action recognition.
470	SCaLE: Supervised and Cascaded Laplacian Eigenmaps for Visual Object Recognition Based on Nearest Neighbors	Ruobing Wu, Yizhou Yu, Wenping Wang	In this paper we develop a novel deep learning method that facilitates examplebased visual object category recognition.