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papers list:

1 iccv-2013-3DNN: Viewpoint Invariant 3D Geometry Matching for Scene Understanding

Author: Scott Satkin, Martial Hebert

Abstract: We present a new algorithm 3DNN (3D NearestNeighbor), which is capable of matching an image with 3D data, independently of the viewpoint from which the image was captured. By leveraging rich annotations associated with each image, our algorithm can automatically produce precise and detailed 3D models of a scene from a single image. Moreover, we can transfer information across images to accurately label and segment objects in a scene. The true benefit of 3DNN compared to a traditional 2D nearest-neighbor approach is that by generalizing across viewpoints, we free ourselves from the need to have training examples captured from all possible viewpoints. Thus, we are able to achieve comparable results using orders of magnitude less data, and recognize objects from never-beforeseen viewpoints. In this work, we describe the 3DNN algorithm and rigorously evaluate its performance for the tasks of geometry estimation and object detection/segmentation. By decoupling the viewpoint and the geometry of an image, we develop a scene matching approach which is truly 100% viewpoint invariant, yielding state-of-the-art performance on challenging data.

2 iccv-2013-3D Scene Understanding by Voxel-CRF

Author: Byung-Soo Kim, Pushmeet Kohli, Silvio Savarese

Abstract: Scene understanding is an important yet very challenging problem in computer vision. In the past few years, researchers have taken advantage of the recent diffusion of depth-RGB (RGB-D) cameras to help simplify the problem of inferring scene semantics. However, while the added 3D geometry is certainly useful to segment out objects with different depth values, it also adds complications in that the 3D geometry is often incorrect because of noisy depth measurements and the actual 3D extent of the objects is usually unknown because of occlusions. In this paper we propose a new method that allows us to jointly refine the 3D reconstruction of the scene (raw depth values) while accurately segmenting out the objects or scene elements from the 3D reconstruction. This is achieved by introducing a new model which we called Voxel-CRF. The Voxel-CRF model is based on the idea of constructing a conditional random field over a 3D volume of interest which captures the semantic and 3D geometric relationships among different elements (voxels) of the scene. Such model allows to jointly estimate (1) a dense voxel-based 3D reconstruction and (2) the semantic labels associated with each voxel even in presence of par- tial occlusions using an approximate yet efficient inference strategy. We evaluated our method on the challenging NYU Depth dataset (Version 1and 2). Experimental results show that our method achieves competitive accuracy in inferring scene semantics and visually appealing results in improving the quality of the 3D reconstruction. We also demonstrate an interesting application of object removal and scene completion from RGB-D images.

3 iccv-2013-3D Sub-query Expansion for Improving Sketch-Based Multi-view Image Retrieval

Author: Yen-Liang Lin, Cheng-Yu Huang, Hao-Jeng Wang, Winston Hsu

Abstract: We propose a 3D sub-query expansion approach for boosting sketch-based multi-view image retrieval. The core idea of our method is to automatically convert two (guided) 2D sketches into an approximated 3D sketch model, and then generate multi-view sketches as expanded sub-queries to improve the retrieval performance. To learn the weights among synthesized views (sub-queries), we present a new multi-query feature to model the similarity between subqueries and dataset images, and formulate it into a convex optimization problem. Our approach shows superior performance compared with the state-of-the-art approach on a public multi-view image dataset. Moreover, we also conduct sensitivity tests to analyze the parameters of our approach based on the gathered user sketches.

4 iccv-2013-ACTIVE: Activity Concept Transitions in Video Event Classification

Author: Chen Sun, Ram Nevatia

Abstract: The goal of high level event classification from videos is to assign a single, high level event label to each query video. Traditional approaches represent each video as a set of low level features and encode it into a fixed length feature vector (e.g. Bag-of-Words), which leave a big gap between low level visual features and high level events. Our paper tries to address this problem by exploiting activity concept transitions in video events (ACTIVE). A video is treated as a sequence of short clips, all of which are observations corresponding to latent activity concept variables in a Hidden Markov Model (HMM). We propose to apply Fisher Kernel techniques so that the concept transitions over time can be encoded into a compact and fixed length feature vector very efficiently. Our approach can utilize concept annotations from independent datasets, and works well even with a very small number of training samples. Experiments on the challenging NIST TRECVID Multimedia Event Detection (MED) dataset shows our approach performs favorably over the state-of-the-art.

5 iccv-2013-A Color Constancy Model with Double-Opponency Mechanisms

Author: Shaobing Gao, Kaifu Yang, Chaoyi Li, Yongjie Li

Abstract: The double-opponent color-sensitive cells in the primary visual cortex (V1) of the human visual system (HVS) have long been recognized as the physiological basis of color constancy. We introduce a new color constancy model by imitating the functional properties of the HVS from the retina to the double-opponent cells in V1. The idea behind the model originates from the observation that the color distribution of the responses of double-opponent cells to the input color-biased images coincides well with the light source direction. Then the true illuminant color of a scene is easily estimated by searching for the maxima of the separate RGB channels of the responses of double-opponent cells in the RGB space. Our systematical experimental evaluations on two commonly used image datasets show that the proposed model can produce competitive results in comparison to the complex state-of-the-art approaches, but with a simple implementation and without the need for training.

6 iccv-2013-A Convex Optimization Framework for Active Learning

Author: Ehsan Elhamifar, Guillermo Sapiro, Allen Yang, S. Shankar Sasrty

Abstract: In many image/video/web classification problems, we have access to a large number of unlabeled samples. However, it is typically expensive and time consuming to obtain labels for the samples. Active learning is the problem of progressively selecting and annotating the most informative unlabeled samples, in order to obtain a high classification performance. Most existing active learning algorithms select only one sample at a time prior to retraining the classifier. Hence, they are computationally expensive and cannot take advantage of parallel labeling systems such as Mechanical Turk. On the other hand, algorithms that allow the selection of multiple samples prior to retraining the classifier, may select samples that have significant information overlap or they involve solving a non-convex optimization. More importantly, the majority of active learning algorithms are developed for a certain classifier type such as SVM. In this paper, we develop an efficient active learning framework based on convex programming, which can select multiple samples at a time for annotation. Unlike the state of the art, our algorithm can be used in conjunction with any type of classifiers, including those of the fam- ily of the recently proposed Sparse Representation-based Classification (SRC). We use the two principles of classifier uncertainty and sample diversity in order to guide the optimization program towards selecting the most informative unlabeled samples, which have the least information overlap. Our method can incorporate the data distribution in the selection process by using the appropriate dissimilarity between pairs of samples. We show the effectiveness of our framework in person detection, scene categorization and face recognition on real-world datasets.

7 iccv-2013-A Deep Sum-Product Architecture for Robust Facial Attributes Analysis

Author: Ping Luo, Xiaogang Wang, Xiaoou Tang

Abstract: Recent works have shown that facial attributes are useful in a number of applications such as face recognition and retrieval. However, estimating attributes in images with large variations remains a big challenge. This challenge is addressed in this paper. Unlike existing methods that assume the independence of attributes during their estimation, our approach captures the interdependencies of local regions for each attribute, as well as the high-order correlations between different attributes, which makes it more robust to occlusions and misdetection of face regions. First, we have modeled region interdependencies with a discriminative decision tree, where each node consists of a detector and a classifier trained on a local region. The detector allows us to locate the region, while the classifier determines the presence or absence of an attribute. Second, correlations of attributes and attribute predictors are modeled by organizing all of the decision trees into a large sum-product network (SPN), which is learned by the EM algorithm and yields the most probable explanation (MPE) of the facial attributes in terms of the region ’s localization and classification. Experimental results on a large data set with 22, 400 images show the effectiveness of the proposed approach.

8 iccv-2013-A Deformable Mixture Parsing Model with Parselets

Author: Jian Dong, Qiang Chen, Wei Xia, Zhongyang Huang, Shuicheng Yan

Abstract: In this work, we address the problem of human parsing, namely partitioning the human body into semantic regions, by using the novel Parselet representation. Previous works often consider solving the problem of human pose estimation as the prerequisite of human parsing. We argue that these approaches cannot obtain optimal pixel level parsing due to the inconsistent targets between these tasks. In this paper, we propose to use Parselets as the building blocks of our parsing model. Parselets are a group of parsable segments which can generally be obtained by lowlevel over-segmentation algorithms and bear strong semantic meaning. We then build a Deformable Mixture Parsing Model (DMPM) for human parsing to simultaneously handle the deformation and multi-modalities of Parselets. The proposed model has two unique characteristics: (1) the possible numerous modalities of Parselet ensembles are exhibited as the “And-Or” structure of sub-trees; (2) to further solve the practical problem of Parselet occlusion or absence, we directly model the visibility property at some leaf nodes. The DMPM thus directly solves the problem of human parsing by searching for the best graph configura- tionfrom apool ofParselet hypotheses without intermediate tasks. Comprehensive evaluations demonstrate the encouraging performance of the proposed approach.

9 iccv-2013-A Flexible Scene Representation for 3D Reconstruction Using an RGB-D Camera

Author: Diego Thomas, Akihiro Sugimoto

Abstract: Updating a global 3D model with live RGB-D measurements has proven to be successful for 3D reconstruction of indoor scenes. Recently, a Truncated Signed Distance Function (TSDF) volumetric model and a fusion algorithm have been introduced (KinectFusion), showing significant advantages such as computational speed and accuracy of the reconstructed scene. This algorithm, however, is expensive in memory when constructing and updating the global model. As a consequence, the method is not well scalable to large scenes. We propose a new flexible 3D scene representation using a set of planes that is cheap in memory use and, nevertheless, achieves accurate reconstruction of indoor scenes from RGB-D image sequences. Projecting the scene onto different planes reduces significantly the size of the scene representation and thus it allows us to generate a global textured 3D model with lower memory requirement while keeping accuracy and easiness to update with live RGB-D measurements. Experimental results demonstrate that our proposed flexible 3D scene representation achieves accurate reconstruction, while keeping the scalability for large indoor scenes.

10 iccv-2013-A Framework for Shape Analysis via Hilbert Space Embedding

Author: Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Harandi

Abstract: We propose a framework for 2D shape analysis using positive definite kernels defined on Kendall’s shape manifold. Different representations of 2D shapes are known to generate different nonlinear spaces. Due to the nonlinearity of these spaces, most existing shape classification algorithms resort to nearest neighbor methods and to learning distances on shape spaces. Here, we propose to map shapes on Kendall’s shape manifold to a high dimensional Hilbert space where Euclidean geometry applies. To this end, we introduce a kernel on this manifold that permits such a mapping, and prove its positive definiteness. This kernel lets us extend kernel-based algorithms developed for Euclidean spaces, such as SVM, MKL and kernel PCA, to the shape manifold. We demonstrate the benefits of our approach over the state-of-the-art methods on shape classification, clustering and retrieval.

11 iccv-2013-A Fully Hierarchical Approach for Finding Correspondences in Non-rigid Shapes

Author: Ivan Sipiran, Benjamin Bustos

Abstract: This paper presents a hierarchical method for finding correspondences in non-rigid shapes. We propose a new representation for 3D meshes: the decomposition tree. This structure characterizes the recursive decomposition process of a mesh into regions of interest and keypoints. The internal nodes contain regions of interest (which may be recursively decomposed) and the leaf nodes contain the keypoints to be matched. We also propose a hierarchical matching algorithm that performs in a level-wise manner. The matching process is guided by the similarity between regions in high levels of the tree, until reaching the keypoints stored in the leaves. This allows us to reduce the search space of correspondences, making also the matching process efficient. We evaluate the effectiveness of our approach using the SHREC’2010 robust correspondence benchmark. In addition, we show that our results outperform the state of the art.

12 iccv-2013-A General Dense Image Matching Framework Combining Direct and Feature-Based Costs

Author: Jim Braux-Zin, Romain Dupont, Adrien Bartoli

Abstract: Dense motion field estimation (typically Romain Dupont1 romain . dupont @ cea . fr Adrien Bartoli2 adrien . bart o l @ gmai l com i . 2 ISIT, Universit e´ d’Auvergne/CNRS, France sions are explicitly modeled [32, 13]. Coarse-to-fine warping improves global convergence by making the assumption that optical flow, the motion of smaller structures is similar to the motion of stereo disparity and surface registration) is a key computer vision problem. Many solutions have been proposed to compute small or large displacements, narrow or wide baseline stereo disparity, but a unified methodology is still lacking. We here introduce a general framework that robustly combines direct and feature-based matching. The feature-based cost is built around a novel robust distance function that handles keypoints and “weak” features such as segments. It allows us to use putative feature matches which may contain mismatches to guide dense motion estimation out of local minima. Our framework uses a robust direct data term (AD-Census). It is implemented with a powerful second order Total Generalized Variation regularization with external and self-occlusion reasoning. Our framework achieves state of the art performance in several cases (standard optical flow benchmarks, wide-baseline stereo and non-rigid surface registration). Our framework has a modular design that customizes to specific application needs.

13 iccv-2013-A General Two-Step Approach to Learning-Based Hashing

Author: Guosheng Lin, Chunhua Shen, David Suter, Anton van_den_Hengel

Abstract: Most existing approaches to hashing apply a single form of hash function, and an optimization process which is typically deeply coupled to this specific form. This tight coupling restricts the flexibility of the method to respond to the data, and can result in complex optimization problems that are difficult to solve. Here we propose a flexible yet simple framework that is able to accommodate different types of loss functions and hash functions. This framework allows a number of existing approaches to hashing to be placed in context, and simplifies the development of new problemspecific hashing methods. Our framework decomposes the hashing learning problem into two steps: hash bit learning and hash function learning based on the learned bits. The first step can typically be formulated as binary quadratic problems, and the second step can be accomplished by training standard binary classifiers. Both problems have been extensively studied in the literature. Our extensive experiments demonstrate that the proposed framework is effective, flexible and outperforms the state-of-the-art.

14 iccv-2013-A Generalized Iterated Shrinkage Algorithm for Non-convex Sparse Coding

Author: Wangmeng Zuo, Deyu Meng, Lei Zhang, Xiangchu Feng, David Zhang

Abstract: In many sparse coding based image restoration and image classification problems, using non-convex ?p-norm minimization (0 ≤ p < 1) can often obtain better results than timhei convex 0?1 -norm m 1)ini camniza otfiteonn. Ab naiunm bbeetrt of algorithms, e.g., iteratively reweighted least squares (IRLS), iteratively thresholding method (ITM-?p), and look-up table (LUT), have been proposed for non-convex ?p-norm sparse coding, while some analytic solutions have been suggested for some specific values of p. In this paper, by extending the popular soft-thresholding operator, we propose a generalized iterated shrinkage algorithm (GISA) for ?p-norm non-convex sparse coding. Unlike the analytic solutions, the proposed GISA algorithm is easy to implement, and can be adopted for solving non-convex sparse coding problems with arbitrary p values. Compared with LUT, GISA is more general and does not need to compute and store the look-up tables. Compared with IRLS and ITM-?p, GISA is theoretically more solid and can achieve more accurate solutions. Experiments on image restoration and sparse coding based face recognition are conducted to validate the performance of GISA. ××

15 iccv-2013-A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks

Author: Yi-Lei Chen, Chiou-Ting Hsu

Abstract: In this paper, we propose a novel low-rank appearance model for removing rain streaks. Different from previous work, our method needs neither rain pixel detection nor time-consuming dictionary learning stage. Instead, as rain streaks usually reveal similar and repeated patterns on imaging scene, we propose and generalize a low-rank model from matrix to tensor structure in order to capture the spatio-temporally correlated rain streaks. With the appearance model, we thus remove rain streaks from image/video (and also other high-order image structure) in a unified way. Our experimental results demonstrate competitive (or even better) visual quality and efficient run-time in comparison with state of the art.

16 iccv-2013-A Generic Deformation Model for Dense Non-rigid Surface Registration: A Higher-Order MRF-Based Approach

Author: Yun Zeng, Chaohui Wang, Xianfeng Gu, Dimitris Samaras, Nikos Paragios

Abstract: We propose a novel approach for dense non-rigid 3D surface registration, which brings together Riemannian geometry and graphical models. To this end, we first introduce a generic deformation model, called Canonical Distortion Coefficients (CDCs), by characterizing the deformation of every point on a surface using the distortions along its two principle directions. This model subsumes the deformation groups commonly used in surface registration such as isometry and conformality, and is able to handle more complex deformations. We also derive its discrete counterpart which can be computed very efficiently in a closed form. Based on these, we introduce a higher-order Markov Random Field (MRF) model which seamlessly integrates our deformation model and a geometry/texture similarity metric. Then we jointly establish the optimal correspondences for all the points via maximum a posteriori (MAP) inference. Moreover, we develop a parallel optimization algorithm to efficiently perform the inference for the proposed higher-order MRF model. The resulting registration algorithm outperforms state-of-the-art methods in both dense non-rigid 3D surface registration and tracking.

17 iccv-2013-A Global Linear Method for Camera Pose Registration

Author: Nianjuan Jiang, Zhaopeng Cui, Ping Tan

Abstract: We present a linear method for global camera pose registration from pairwise relative poses encoded in essential matrices. Our method minimizes an approximate geometric error to enforce the triangular relationship in camera triplets. This formulation does not suffer from the typical ‘unbalanced scale ’ problem in linear methods relying on pairwise translation direction constraints, i.e. an algebraic error; nor the system degeneracy from collinear motion. In the case of three cameras, our method provides a good linear approximation of the trifocal tensor. It can be directly scaled up to register multiple cameras. The results obtained are accurate for point triangulation and can serve as a good initialization for final bundle adjustment. We evaluate the algorithm performance with different types of data and demonstrate its effectiveness. Our system produces good accuracy, robustness, and outperforms some well-known systems on efficiency.

18 iccv-2013-A Joint Intensity and Depth Co-sparse Analysis Model for Depth Map Super-resolution

Author: Martin Kiechle, Simon Hawe, Martin Kleinsteuber

Abstract: High-resolution depth maps can be inferred from lowresolution depth measurements and an additional highresolution intensity image of the same scene. To that end, we introduce a bimodal co-sparse analysis model, which is able to capture the interdependency of registered intensity . go l e i um . de . .t ities together with the knowledge of the relative positions between all views. Despite very active research in this area and significant improvements over the past years, stereo methods still struggle with noise, texture-less regions, repetitive texture, and occluded areas. For an overview of stereo methods, the reader is referred to [25]. and depth information. This model is based on the assumption that the co-supports of corresponding bimodal image structures are aligned when computed by a suitable pair of analysis operators. No analytic form of such operators ex- ist and we propose a method for learning them from a set of registered training signals. This learning process is done offline and returns a bimodal analysis operator that is universally applicable to natural scenes. We use this to exploit the bimodal co-sparse analysis model as a prior for solving inverse problems, which leads to an efficient algorithm for depth map super-resolution.

19 iccv-2013-A Learning-Based Approach to Reduce JPEG Artifacts in Image Matting

Author: Inchang Choi, Sunyeong Kim, Michael S. Brown, Yu-Wing Tai

Abstract: Single image matting techniques assume high-quality input images. The vast majority of images on the web and in personal photo collections are encoded using JPEG compression. JPEG images exhibit quantization artifacts that adversely affect the performance of matting algorithms. To address this situation, we propose a learning-based post-processing method to improve the alpha mattes extracted from JPEG images. Our approach learns a set of sparse dictionaries from training examples that are used to transfer details from high-quality alpha mattes to alpha mattes corrupted by JPEG compression. Three different dictionaries are defined to accommodate different object structure (long hair, short hair, and sharp boundaries). A back-projection criteria combined within an MRF framework is used to automatically select the best dictionary to apply on the object’s local boundary. We demonstrate that our method can produces superior results over existing state-of-the-art matting algorithms on a variety of inputs and compression levels.

20 iccv-2013-A Max-Margin Perspective on Sparse Representation-Based Classification

Author: Zhaowen Wang, Jianchao Yang, Nasser Nasrabadi, Thomas Huang

Abstract: Sparse Representation-based Classification (SRC) is a powerful tool in distinguishing signal categories which lie on different subspaces. Despite its wide application to visual recognition tasks, current understanding of SRC is solely based on a reconstructive perspective, which neither offers any guarantee on its classification performance nor provides any insight on how to design a discriminative dictionary for SRC. In this paper, we present a novel perspective towards SRC and interpret it as a margin classifier. The decision boundary and margin of SRC are analyzed in local regions where the support of sparse code is stable. Based on the derived margin, we propose a hinge loss function as the gauge for the classification performance of SRC. A stochastic gradient descent algorithm is implemented to maximize the margin of SRC and obtain more discriminative dictionaries. Experiments validate the effectiveness of the proposed approach in predicting classification performance and improving dictionary quality over reconstructive ones. Classification results competitive with other state-ofthe-art sparse coding methods are reported on several data sets.

21 iccv-2013-A Method of Perceptual-Based Shape Decomposition

22 iccv-2013-A New Adaptive Segmental Matching Measure for Human Activity Recognition

23 iccv-2013-A New Image Quality Metric for Image Auto-denoising

24 iccv-2013-A Non-parametric Bayesian Network Prior of Human Pose

25 iccv-2013-A Novel Earth Mover's Distance Methodology for Image Matching with Gaussian Mixture Models

26 iccv-2013-A Practical Transfer Learning Algorithm for Face Verification

27 iccv-2013-A Robust Analytical Solution to Isometric Shape-from-Template with Focal Length Calibration

28 iccv-2013-A Rotational Stereo Model Based on XSlit Imaging

29 iccv-2013-A Scalable Unsupervised Feature Merging Approach to Efficient Dimensionality Reduction of High-Dimensional Visual Data

30 iccv-2013-A Simple Model for Intrinsic Image Decomposition with Depth Cues

31 iccv-2013-A Unified Probabilistic Approach Modeling Relationships between Attributes and Objects

32 iccv-2013-A Unified Rolling Shutter and Motion Blur Model for 3D Visual Registration

33 iccv-2013-A Unified Video Segmentation Benchmark: Annotation, Metrics and Analysis

34 iccv-2013-Abnormal Event Detection at 150 FPS in MATLAB

35 iccv-2013-Accurate Blur Models vs. Image Priors in Single Image Super-resolution

36 iccv-2013-Accurate and Robust 3D Facial Capture Using a Single RGBD Camera

37 iccv-2013-Action Recognition and Localization by Hierarchical Space-Time Segments

38 iccv-2013-Action Recognition with Actons

39 iccv-2013-Action Recognition with Improved Trajectories

40 iccv-2013-Action and Event Recognition with Fisher Vectors on a Compact Feature Set

41 iccv-2013-Active Learning of an Action Detector from Untrimmed Videos

42 iccv-2013-Active MAP Inference in CRFs for Efficient Semantic Segmentation

43 iccv-2013-Active Visual Recognition with Expertise Estimation in Crowdsourcing

44 iccv-2013-Adapting Classification Cascades to New Domains

45 iccv-2013-Affine-Constrained Group Sparse Coding and Its Application to Image-Based Classifications

46 iccv-2013-Allocentric Pose Estimation

47 iccv-2013-Alternating Regression Forests for Object Detection and Pose Estimation

48 iccv-2013-An Adaptive Descriptor Design for Object Recognition in the Wild

49 iccv-2013-An Enhanced Structure-from-Motion Paradigm Based on the Absolute Dual Quadric and Images of Circular Points

50 iccv-2013-Analysis of Scores, Datasets, and Models in Visual Saliency Prediction

51 iccv-2013-Anchored Neighborhood Regression for Fast Example-Based Super-Resolution

52 iccv-2013-Attribute Adaptation for Personalized Image Search

53 iccv-2013-Attribute Dominance: What Pops Out?

54 iccv-2013-Attribute Pivots for Guiding Relevance Feedback in Image Search

55 iccv-2013-Automatic Kronecker Product Model Based Detection of Repeated Patterns in 2D Urban Images

56 iccv-2013-Automatic Registration of RGB-D Scans via Salient Directions

57 iccv-2013-BOLD Features to Detect Texture-less Objects

58 iccv-2013-Bayesian 3D Tracking from Monocular Video

59 iccv-2013-Bayesian Joint Topic Modelling for Weakly Supervised Object Localisation

60 iccv-2013-Bayesian Robust Matrix Factorization for Image and Video Processing

61 iccv-2013-Beyond Hard Negative Mining: Efficient Detector Learning via Block-Circulant Decomposition

62 iccv-2013-Bird Part Localization Using Exemplar-Based Models with Enforced Pose and Subcategory Consistency

63 iccv-2013-Bounded Labeling Function for Global Segmentation of Multi-part Objects with Geometric Constraints

64 iccv-2013-Box in the Box: Joint 3D Layout and Object Reasoning from Single Images

65 iccv-2013-Breaking the Chain: Liberation from the Temporal Markov Assumption for Tracking Human Poses

66 iccv-2013-Building Part-Based Object Detectors via 3D Geometry

67 iccv-2013-Calibration-Free Gaze Estimation Using Human Gaze Patterns

68 iccv-2013-Camera Alignment Using Trajectory Intersections in Unsynchronized Videos

69 iccv-2013-Capturing Global Semantic Relationships for Facial Action Unit Recognition

70 iccv-2013-Cascaded Shape Space Pruning for Robust Facial Landmark Detection

71 iccv-2013-Category-Independent Object-Level Saliency Detection

72 iccv-2013-Characterizing Layouts of Outdoor Scenes Using Spatial Topic Processes

73 iccv-2013-Class-Specific Simplex-Latent Dirichlet Allocation for Image Classification

74 iccv-2013-Co-segmentation by Composition

75 iccv-2013-CoDeL: A Human Co-detection and Labeling Framework

76 iccv-2013-Coarse-to-Fine Semantic Video Segmentation Using Supervoxel Trees

77 iccv-2013-Codemaps - Segment, Classify and Search Objects Locally

78 iccv-2013-Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations

79 iccv-2013-Coherent Object Detection with 3D Geometric Context from a Single Image

80 iccv-2013-Collaborative Active Learning of a Kernel Machine Ensemble for Recognition

81 iccv-2013-Combining the Right Features for Complex Event Recognition

82 iccv-2013-Compensating for Motion during Direct-Global Separation

83 iccv-2013-Complementary Projection Hashing

84 iccv-2013-Complex 3D General Object Reconstruction from Line Drawings

85 iccv-2013-Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach

86 iccv-2013-Concurrent Action Detection with Structural Prediction

87 iccv-2013-Conservation Tracking

88 iccv-2013-Constant Time Weighted Median Filtering for Stereo Matching and Beyond

89 iccv-2013-Constructing Adaptive Complex Cells for Robust Visual Tracking

90 iccv-2013-Content-Aware Rotation

91 iccv-2013-Contextual Hypergraph Modeling for Salient Object Detection

92 iccv-2013-Corrected-Moment Illuminant Estimation

93 iccv-2013-Correlation Adaptive Subspace Segmentation by Trace Lasso

94 iccv-2013-Correntropy Induced L2 Graph for Robust Subspace Clustering

95 iccv-2013-Cosegmentation and Cosketch by Unsupervised Learning

96 iccv-2013-Coupled Dictionary and Feature Space Learning with Applications to Cross-Domain Image Synthesis and Recognition

97 iccv-2013-Coupling Alignments with Recognition for Still-to-Video Face Recognition

98 iccv-2013-Cross-Field Joint Image Restoration via Scale Map

99 iccv-2013-Cross-View Action Recognition over Heterogeneous Feature Spaces

100 iccv-2013-Curvature-Aware Regularization on Riemannian Submanifolds

101 iccv-2013-DCSH - Matching Patches in RGBD Images

102 iccv-2013-Data-Driven 3D Primitives for Single Image Understanding

103 iccv-2013-Deblurring by Example Using Dense Correspondence

104 iccv-2013-Decomposing Bag of Words Histograms

105 iccv-2013-DeepFlow: Large Displacement Optical Flow with Deep Matching

106 iccv-2013-Deep Learning Identity-Preserving Face Space

107 iccv-2013-Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction

108 iccv-2013-Depth from Combining Defocus and Correspondence Using Light-Field Cameras

109 iccv-2013-Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going?

110 iccv-2013-Detecting Curved Symmetric Parts Using a Deformable Disc Model

111 iccv-2013-Detecting Dynamic Objects with Multi-view Background Subtraction

112 iccv-2013-Detecting Irregular Curvilinear Structures in Gray Scale and Color Imagery Using Multi-directional Oriented Flux

113 iccv-2013-Deterministic Fitting of Multiple Structures Using Iterative MaxFS with Inlier Scale Estimation

114 iccv-2013-Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution

115 iccv-2013-Direct Optimization of Frame-to-Frame Rotation

116 iccv-2013-Directed Acyclic Graph Kernels for Action Recognition

117 iccv-2013-Discovering Details and Scene Structure with Hierarchical Iconoid Shift

118 iccv-2013-Discovering Object Functionality

119 iccv-2013-Discriminant Tracking Using Tensor Representation with Semi-supervised Improvement

120 iccv-2013-Discriminative Label Propagation for Multi-object Tracking with Sporadic Appearance Features

121 iccv-2013-Discriminatively Trained Templates for 3D Object Detection: A Real Time Scalable Approach

122 iccv-2013-Distributed Low-Rank Subspace Segmentation

123 iccv-2013-Domain Adaptive Classification

124 iccv-2013-Domain Transfer Support Vector Ranking for Person Re-identification without Target Camera Label Information

125 iccv-2013-Drosophila Embryo Stage Annotation Using Label Propagation

126 iccv-2013-Dynamic Label Propagation for Semi-supervised Multi-class Multi-label Classification

127 iccv-2013-Dynamic Pooling for Complex Event Recognition

128 iccv-2013-Dynamic Probabilistic Volumetric Models

129 iccv-2013-Dynamic Scene Deblurring

130 iccv-2013-Dynamic Structured Model Selection

131 iccv-2013-EVSAC: Accelerating Hypotheses Generation by Modeling Matching Scores with Extreme Value Theory

132 iccv-2013-Efficient 3D Scene Labeling Using Fields of Trees

133 iccv-2013-Efficient Hand Pose Estimation from a Single Depth Image

134 iccv-2013-Efficient Higher-Order Clustering on the Grassmann Manifold

135 iccv-2013-Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

136 iccv-2013-Efficient Pedestrian Detection by Directly Optimizing the Partial Area under the ROC Curve

137 iccv-2013-Efficient Salient Region Detection with Soft Image Abstraction

138 iccv-2013-Efficient and Robust Large-Scale Rotation Averaging

139 iccv-2013-Elastic Fragments for Dense Scene Reconstruction

140 iccv-2013-Elastic Net Constraints for Shape Matching

141 iccv-2013-Enhanced Continuous Tabu Search for Parameter Estimation in Multiview Geometry

142 iccv-2013-Ensemble Projection for Semi-supervised Image Classification

143 iccv-2013-Estimating Human Pose with Flowing Puppets

144 iccv-2013-Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors

145 iccv-2013-Estimating the Material Properties of Fabric from Video

146 iccv-2013-Event Detection in Complex Scenes Using Interval Temporal Constraints

147 iccv-2013-Event Recognition in Photo Collections with a Stopwatch HMM

148 iccv-2013-Example-Based Facade Texture Synthesis

149 iccv-2013-Exemplar-Based Graph Matching for Robust Facial Landmark Localization

150 iccv-2013-Exemplar Cut

151 iccv-2013-Exploiting Reflection Change for Automatic Reflection Removal

152 iccv-2013-Extrinsic Camera Calibration without a Direct View Using Spherical Mirror

153 iccv-2013-Face Recognition Using Face Patch Networks

154 iccv-2013-Face Recognition via Archetype Hull Ranking

155 iccv-2013-Facial Action Unit Event Detection by Cascade of Tasks

156 iccv-2013-Fast Direct Super-Resolution by Simple Functions

157 iccv-2013-Fast Face Detector Training Using Tailored Views

158 iccv-2013-Fast High Dimensional Vector Multiplication Face Recognition

159 iccv-2013-Fast Neighborhood Graph Search Using Cartesian Concatenation

160 iccv-2013-Fast Object Segmentation in Unconstrained Video

161 iccv-2013-Fast Sparsity-Based Orthogonal Dictionary Learning for Image Restoration

162 iccv-2013-Fast Subspace Search via Grassmannian Based Hashing

163 iccv-2013-Feature Weighting via Optimal Thresholding for Video Analysis

164 iccv-2013-Fibonacci Exposure Bracketing for High Dynamic Range Imaging

165 iccv-2013-Find the Best Path: An Efficient and Accurate Classifier for Image Hierarchies

166 iccv-2013-Finding Actors and Actions in Movies

167 iccv-2013-Finding Causal Interactions in Video Sequences

168 iccv-2013-Finding the Best from the Second Bests - Inhibiting Subjective Bias in Evaluation of Visual Tracking Algorithms

169 iccv-2013-Fine-Grained Categorization by Alignments

170 iccv-2013-Fingerspelling Recognition with Semi-Markov Conditional Random Fields

171 iccv-2013-Fix Structured Learning of 2013 ICCV paper k2opt.pdf

172 iccv-2013-Flattening Supervoxel Hierarchies by the Uniform Entropy Slice

173 iccv-2013-Fluttering Pattern Generation Using Modified Legendre Sequence for Coded Exposure Imaging

174 iccv-2013-Forward Motion Deblurring

175 iccv-2013-From Actemes to Action: A Strongly-Supervised Representation for Detailed Action Understanding

176 iccv-2013-From Large Scale Image Categorization to Entry-Level Categories

177 iccv-2013-From Point to Set: Extend the Learning of Distance Metrics

178 iccv-2013-From Semi-supervised to Transfer Counting of Crowds

179 iccv-2013-From Subcategories to Visual Composites: A Multi-level Framework for Object Detection

180 iccv-2013-From Where and How to What We See

181 iccv-2013-Frustratingly Easy NBNN Domain Adaptation

182 iccv-2013-GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity

183 iccv-2013-Geometric Registration Based on Distortion Estimation

184 iccv-2013-Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion

185 iccv-2013-Go-ICP: Solving 3D Registration Efficiently and Globally Optimally

186 iccv-2013-GrabCut in One Cut

187 iccv-2013-Group Norm for Learning Structured SVMs with Unstructured Latent Variables

188 iccv-2013-Group Sparsity and Geometry Constrained Dictionary Learning for Action Recognition from Depth Maps

189 iccv-2013-HOGgles: Visualizing Object Detection Features

190 iccv-2013-Handling Occlusions with Franken-Classifiers

191 iccv-2013-Handling Uncertain Tags in Visual Recognition

192 iccv-2013-Handwritten Word Spotting with Corrected Attributes

193 iccv-2013-Heterogeneous Auto-similarities of Characteristics (HASC): Exploiting Relational Information for Classification

194 iccv-2013-Heterogeneous Image Features Integration via Multi-modal Semi-supervised Learning Model

195 iccv-2013-Hidden Factor Analysis for Age Invariant Face Recognition

196 iccv-2013-Hierarchical Data-Driven Descent for Efficient Optimal Deformation Estimation

197 iccv-2013-Hierarchical Joint Max-Margin Learning of Mid and Top Level Representations for Visual Recognition

198 iccv-2013-Hierarchical Part Matching for Fine-Grained Visual Categorization

199 iccv-2013-High Quality Shape from a Single RGB-D Image under Uncalibrated Natural Illumination

200 iccv-2013-Higher Order Matching for Consistent Multiple Target Tracking

201 iccv-2013-Holistic Scene Understanding for 3D Object Detection with RGBD Cameras

202 iccv-2013-How Do You Tell a Blackbird from a Crow?

203 iccv-2013-How Related Exemplars Help Complex Event Detection in Web Videos?

204 iccv-2013-Human Attribute Recognition by Rich Appearance Dictionary

205 iccv-2013-Human Re-identification by Matching Compositional Template with Cluster Sampling

206 iccv-2013-Hybrid Deep Learning for Face Verification

207 iccv-2013-Illuminant Chromaticity from Image Sequences

208 iccv-2013-Image Co-segmentation via Consistent Functional Maps

209 iccv-2013-Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation

210 iccv-2013-Image Retrieval Using Textual Cues

211 iccv-2013-Image Segmentation with Cascaded Hierarchical Models and Logistic Disjunctive Normal Networks

212 iccv-2013-Image Set Classification Using Holistic Multiple Order Statistics Features and Localized Multi-kernel Metric Learning

213 iccv-2013-Implied Feedback: Learning Nuances of User Behavior in Image Search

214 iccv-2013-Improving Graph Matching via Density Maximization

215 iccv-2013-Incorporating Cloud Distribution in Sky Representation

216 iccv-2013-Inferring "Dark Matter" and "Dark Energy" from Videos

217 iccv-2013-Initialization-Insensitive Visual Tracking through Voting with Salient Local Features

218 iccv-2013-Interactive Markerless Articulated Hand Motion Tracking Using RGB and Depth Data

219 iccv-2013-Internet Based Morphable Model

220 iccv-2013-Joint Deep Learning for Pedestrian Detection

221 iccv-2013-Joint Inverted Indexing

222 iccv-2013-Joint Learning of Discriminative Prototypes and Large Margin Nearest Neighbor Classifiers

223 iccv-2013-Joint Noise Level Estimation from Personal Photo Collections

224 iccv-2013-Joint Optimization for Consistent Multiple Graph Matching

225 iccv-2013-Joint Segmentation and Pose Tracking of Human in Natural Videos

226 iccv-2013-Joint Subspace Stabilization for Stereoscopic Video

227 iccv-2013-Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning

228 iccv-2013-Large-Scale Multi-resolution Surface Reconstruction from RGB-D Sequences

229 iccv-2013-Large-Scale Video Hashing via Structure Learning

230 iccv-2013-Latent Data Association: Bayesian Model Selection for Multi-target Tracking

231 iccv-2013-Latent Multitask Learning for View-Invariant Action Recognition

232 iccv-2013-Latent Space Sparse Subspace Clustering

233 iccv-2013-Latent Task Adaptation with Large-Scale Hierarchies

234 iccv-2013-Learning CRFs for Image Parsing with Adaptive Subgradient Descent

235 iccv-2013-Learning Coupled Feature Spaces for Cross-Modal Matching

236 iccv-2013-Learning Discriminative Part Detectors for Image Classification and Cosegmentation

237 iccv-2013-Learning Graph Matching: Oriented to Category Modeling from Cluttered Scenes

238 iccv-2013-Learning Graphs to Match

239 iccv-2013-Learning Hash Codes with Listwise Supervision

240 iccv-2013-Learning Maximum Margin Temporal Warping for Action Recognition

241 iccv-2013-Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection

242 iccv-2013-Learning People Detectors for Tracking in Crowded Scenes

243 iccv-2013-Learning Slow Features for Behaviour Analysis

244 iccv-2013-Learning View-Invariant Sparse Representations for Cross-View Action Recognition

245 iccv-2013-Learning a Dictionary of Shape Epitomes with Applications to Image Labeling

246 iccv-2013-Learning the Visual Interpretation of Sentences

247 iccv-2013-Learning to Predict Gaze in Egocentric Video

248 iccv-2013-Learning to Rank Using Privileged Information

249 iccv-2013-Learning to Share Latent Tasks for Action Recognition

250 iccv-2013-Lifting 3D Manhattan Lines from a Single Image

251 iccv-2013-Like Father, Like Son: Facial Expression Dynamics for Kinship Verification

252 iccv-2013-Line Assisted Light Field Triangulation and Stereo Matching

253 iccv-2013-Linear Sequence Discriminant Analysis: A Model-Based Dimensionality Reduction Method for Vector Sequences

254 iccv-2013-Live Metric 3D Reconstruction on Mobile Phones

255 iccv-2013-Local Signal Equalization for Correspondence Matching

256 iccv-2013-Locally Affine Sparse-to-Dense Matching for Motion and Occlusion Estimation

257 iccv-2013-Log-Euclidean Kernels for Sparse Representation and Dictionary Learning

258 iccv-2013-Low-Rank Sparse Coding for Image Classification

259 iccv-2013-Manifold Based Face Synthesis from Sparse Samples

260 iccv-2013-Manipulation Pattern Discovery: A Nonparametric Bayesian Approach

261 iccv-2013-Markov Network-Based Unified Classifier for Face Identification

262 iccv-2013-Matching Dry to Wet Materials

263 iccv-2013-Measuring Flow Complexity in Videos

264 iccv-2013-Minimal Basis Facility Location for Subspace Segmentation

265 iccv-2013-Mining Motion Atoms and Phrases for Complex Action Recognition

266 iccv-2013-Mining Multiple Queries for Image Retrieval: On-the-Fly Learning of an Object-Specific Mid-level Representation

267 iccv-2013-Model Recommendation with Virtual Probes for Egocentric Hand Detection

268 iccv-2013-Modeling 4D Human-Object Interactions for Event and Object Recognition

269 iccv-2013-Modeling Occlusion by Discriminative AND-OR Structures

270 iccv-2013-Modeling Self-Occlusions in Dynamic Shape and Appearance Tracking

271 iccv-2013-Modeling the Calibration Pipeline of the Lytro Camera for High Quality Light-Field Image Reconstruction

272 iccv-2013-Modifying the Memorability of Face Photographs

273 iccv-2013-Monocular Image 3D Human Pose Estimation under Self-Occlusion

274 iccv-2013-Monte Carlo Tree Search for Scheduling Activity Recognition

275 iccv-2013-Motion-Aware KNN Laplacian for Video Matting

276 iccv-2013-Multi-attributed Dictionary Learning for Sparse Coding

277 iccv-2013-Multi-channel Correlation Filters

278 iccv-2013-Multi-scale Topological Features for Hand Posture Representation and Analysis

279 iccv-2013-Multi-stage Contextual Deep Learning for Pedestrian Detection

280 iccv-2013-Multi-view 3D Reconstruction from Uncalibrated Radially-Symmetric Cameras

281 iccv-2013-Multi-view Normal Field Integration for 3D Reconstruction of Mirroring Objects

282 iccv-2013-Multi-view Object Segmentation in Space and Time

283 iccv-2013-Multiple Non-rigid Surface Detection and Registration

284 iccv-2013-Multiview Photometric Stereo Using Planar Mesh Parameterization

285 iccv-2013-NEIL: Extracting Visual Knowledge from Web Data

286 iccv-2013-NYC3DCars: A Dataset of 3D Vehicles in Geographic Context

287 iccv-2013-Neighbor-to-Neighbor Search for Fast Coding of Feature Vectors

288 iccv-2013-Nested Shape Descriptors

289 iccv-2013-Network Principles for SfM: Disambiguating Repeated Structures with Local Context

290 iccv-2013-New Graph Structured Sparsity Model for Multi-label Image Annotations

291 iccv-2013-No Matter Where You Are: Flexible Graph-Guided Multi-task Learning for Multi-view Head Pose Classification under Target Motion

292 iccv-2013-Non-convex P-Norm Projection for Robust Sparsity

293 iccv-2013-Nonparametric Blind Super-resolution

294 iccv-2013-Offline Mobile Instance Retrieval with a Small Memory Footprint

295 iccv-2013-On One-Shot Similarity Kernels: Explicit Feature Maps and Properties

296 iccv-2013-On the Mean Curvature Flow on Graphs with Applications in Image and Manifold Processing

297 iccv-2013-Online Motion Segmentation Using Dynamic Label Propagation

298 iccv-2013-Online Robust Non-negative Dictionary Learning for Visual Tracking

299 iccv-2013-Online Video SEEDS for Temporal Window Objectness

300 iccv-2013-Optical Flow via Locally Adaptive Fusion of Complementary Data Costs

301 iccv-2013-Optimal Orthogonal Basis and Image Assimilation: Motion Modeling

302 iccv-2013-Optimization Problems for Fast AAM Fitting in-the-Wild

303 iccv-2013-Orderless Tracking through Model-Averaged Posterior Estimation

304 iccv-2013-PM-Huber: PatchMatch with Huber Regularization for Stereo Matching

305 iccv-2013-POP: Person Re-identification Post-rank Optimisation

306 iccv-2013-Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items

307 iccv-2013-Parallel Transport of Deformations in Shape Space of Elastic Surfaces

308 iccv-2013-Parsing IKEA Objects: Fine Pose Estimation

309 iccv-2013-Partial Enumeration and Curvature Regularization

310 iccv-2013-Partial Sum Minimization of Singular Values in RPCA for Low-Level Vision

311 iccv-2013-Pedestrian Parsing via Deep Decompositional Network

312 iccv-2013-Perceptual Fidelity Aware Mean Squared Error

313 iccv-2013-Person Re-identification by Salience Matching

314 iccv-2013-Perspective Motion Segmentation via Collaborative Clustering

315 iccv-2013-PhotoOCR: Reading Text in Uncontrolled Conditions

316 iccv-2013-Pictorial Human Spaces: How Well Do Humans Perceive a 3D Articulated Pose?

317 iccv-2013-Piecewise Rigid Scene Flow

318 iccv-2013-PixelTrack: A Fast Adaptive Algorithm for Tracking Non-rigid Objects

319 iccv-2013-Point-Based 3D Reconstruction of Thin Objects

320 iccv-2013-Pose-Configurable Generic Tracking of Elongated Objects

321 iccv-2013-Pose-Free Facial Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Shape Model

322 iccv-2013-Pose Estimation and Segmentation of People in 3D Movies

323 iccv-2013-Pose Estimation with Unknown Focal Length Using Points, Directions and Lines

324 iccv-2013-Potts Model, Parametric Maxflow and K-Submodular Functions

325 iccv-2013-Predicting Primary Gaze Behavior Using Social Saliency Fields

326 iccv-2013-Predicting Sufficient Annotation Strength for Interactive Foreground Segmentation

327 iccv-2013-Predicting an Object Location Using a Global Image Representation

328 iccv-2013-Probabilistic Elastic Part Model for Unsupervised Face Detector Adaptation

329 iccv-2013-Progressive Multigrid Eigensolvers for Multiscale Spectral Segmentation

330 iccv-2013-Proportion Priors for Image Sequence Segmentation

331 iccv-2013-Pyramid Coding for Functional Scene Element Recognition in Video Scenes

332 iccv-2013-Quadruplet-Wise Image Similarity Learning

333 iccv-2013-Quantize and Conquer: A Dimensionality-Recursive Solution to Clustering, Vector Quantization, and Image Retrieval

334 iccv-2013-Query-Adaptive Asymmetrical Dissimilarities for Visual Object Retrieval

335 iccv-2013-Random Faces Guided Sparse Many-to-One Encoder for Pose-Invariant Face Recognition

336 iccv-2013-Random Forests of Local Experts for Pedestrian Detection

337 iccv-2013-Random Grids: Fast Approximate Nearest Neighbors and Range Searching for Image Search

338 iccv-2013-Randomized Ensemble Tracking

339 iccv-2013-Rank Minimization across Appearance and Shape for AAM Ensemble Fitting

340 iccv-2013-Real-Time Articulated Hand Pose Estimation Using Semi-supervised Transductive Regression Forests

341 iccv-2013-Real-Time Body Tracking with One Depth Camera and Inertial Sensors

342 iccv-2013-Real-Time Solution to the Absolute Pose Problem with Unknown Radial Distortion and Focal Length

343 iccv-2013-Real-World Normal Map Capture for Nearly Flat Reflective Surfaces

344 iccv-2013-Recognising Human-Object Interaction via Exemplar Based Modelling

345 iccv-2013-Recognizing Text with Perspective Distortion in Natural Scenes

346 iccv-2013-Rectangling Stereographic Projection for Wide-Angle Image Visualization

347 iccv-2013-Recursive Estimation of the Stein Center of SPD Matrices and Its Applications

348 iccv-2013-Refractive Structure-from-Motion on Underwater Images

349 iccv-2013-Regionlets for Generic Object Detection

350 iccv-2013-Relative Attributes for Large-Scale Abandoned Object Detection

351 iccv-2013-Restoring an Image Taken through a Window Covered with Dirt or Rain

352 iccv-2013-Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees

353 iccv-2013-Revisiting the PnP Problem: A Fast, General and Optimal Solution

354 iccv-2013-Robust Dictionary Learning by Error Source Decomposition

355 iccv-2013-Robust Face Landmark Estimation under Occlusion

356 iccv-2013-Robust Feature Set Matching for Partial Face Recognition

357 iccv-2013-Robust Matrix Factorization with Unknown Noise

358 iccv-2013-Robust Non-parametric Data Fitting for Correspondence Modeling

359 iccv-2013-Robust Object Tracking with Online Multi-lifespan Dictionary Learning

360 iccv-2013-Robust Subspace Clustering via Half-Quadratic Minimization

361 iccv-2013-Robust Trajectory Clustering for Motion Segmentation

362 iccv-2013-Robust Tucker Tensor Decomposition for Effective Image Representation

363 iccv-2013-Rolling Shutter Stereo

364 iccv-2013-SGTD: Structure Gradient and Texture Decorrelating Regularization for Image Decomposition

365 iccv-2013-SIFTpack: A Compact Representation for Efficient SIFT Matching

366 iccv-2013-STAR3D: Simultaneous Tracking and Reconstruction of 3D Objects Using RGB-D Data

367 iccv-2013-SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels

368 iccv-2013-SYM-FISH: A Symmetry-Aware Flip Invariant Sketch Histogram Shape Descriptor

369 iccv-2013-Saliency Detection: A Boolean Map Approach

370 iccv-2013-Saliency Detection in Large Point Sets

371 iccv-2013-Saliency Detection via Absorbing Markov Chain

372 iccv-2013-Saliency Detection via Dense and Sparse Reconstruction

373 iccv-2013-Saliency and Human Fixations: State-of-the-Art and Study of Comparison Metrics

374 iccv-2013-Salient Region Detection by UFO: Uniqueness, Focusness and Objectness

375 iccv-2013-Scene Collaging: Analysis and Synthesis of Natural Images with Semantic Layers

376 iccv-2013-Scene Text Localization and Recognition with Oriented Stroke Detection

377 iccv-2013-Segmentation Driven Object Detection with Fisher Vectors

378 iccv-2013-Semantic-Aware Co-indexing for Image Retrieval

379 iccv-2013-Semantic Segmentation without Annotating Segments

380 iccv-2013-Semantic Transform: Weakly Supervised Semantic Inference for Relating Visual Attributes

381 iccv-2013-Semantically-Based Human Scanpath Estimation with HMMs

382 iccv-2013-Semi-dense Visual Odometry for a Monocular Camera

383 iccv-2013-Semi-supervised Learning for Large Scale Image Cosegmentation

384 iccv-2013-Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization

385 iccv-2013-Separating Reflective and Fluorescent Components Using High Frequency Illumination in the Spectral Domain

386 iccv-2013-Sequential Bayesian Model Update under Structured Scene Prior for Semantic Road Scenes Labeling

387 iccv-2013-Shape Anchors for Data-Driven Multi-view Reconstruction

388 iccv-2013-Shape Index Descriptors Applied to Texture-Based Galaxy Analysis

389 iccv-2013-Shortest Paths with Curvature and Torsion

390 iccv-2013-Shufflets: Shared Mid-level Parts for Fast Object Detection

391 iccv-2013-Sieving Regression Forest Votes for Facial Feature Detection in the Wild

392 iccv-2013-Similarity Metric Learning for Face Recognition

393 iccv-2013-Simultaneous Clustering and Tracklet Linking for Multi-face Tracking in Videos

394 iccv-2013-Single-Patch Low-Rank Prior for Non-pointwise Impulse Noise Removal

395 iccv-2013-Slice Sampling Particle Belief Propagation

396 iccv-2013-Space-Time Robust Representation for Action Recognition

397 iccv-2013-Space-Time Tradeoffs in Photo Sequencing

398 iccv-2013-Sparse Variation Dictionary Learning for Face Recognition with a Single Training Sample per Person

399 iccv-2013-Spoken Attributes: Mixing Binary and Relative Attributes to Say the Right Thing

400 iccv-2013-Stable Hyper-pooling and Query Expansion for Event Detection

401 iccv-2013-Stacked Predictive Sparse Coding for Classification of Distinct Regions in Tumor Histopathology

402 iccv-2013-Street View Motion-from-Structure-from-Motion

403 iccv-2013-Strong Appearance and Expressive Spatial Models for Human Pose Estimation

404 iccv-2013-Structured Forests for Fast Edge Detection

405 iccv-2013-Structured Light in Sunlight

406 iccv-2013-Style-Aware Mid-level Representation for Discovering Visual Connections in Space and Time

407 iccv-2013-Subpixel Scanning Invariant to Indirect Lighting Using Quadratic Code Length

408 iccv-2013-Super-resolution via Transform-Invariant Group-Sparse Regularization

409 iccv-2013-Supervised Binary Hash Code Learning with Jensen Shannon Divergence

410 iccv-2013-Support Surface Prediction in Indoor Scenes

411 iccv-2013-Symbiotic Segmentation and Part Localization for Fine-Grained Categorization

412 iccv-2013-Synergistic Clustering of Image and Segment Descriptors for Unsupervised Scene Understanding

413 iccv-2013-Target-Driven Moire Pattern Synthesis by Phase Modulation

414 iccv-2013-Temporally Consistent Superpixels

415 iccv-2013-Text Localization in Natural Images Using Stroke Feature Transform and Text Covariance Descriptors

416 iccv-2013-The Interestingness of Images

417 iccv-2013-The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection

418 iccv-2013-The Way They Move: Tracking Multiple Targets with Similar Appearance

419 iccv-2013-To Aggregate or Not to aggregate: Selective Match Kernels for Image Search

420 iccv-2013-Topology-Constrained Layered Tracking with Latent Flow

421 iccv-2013-Total Variation Regularization for Functions with Values in a Manifold

422 iccv-2013-Toward Guaranteed Illumination Models for Non-convex Objects

423 iccv-2013-Towards Motion Aware Light Field Video for Dynamic Scenes

424 iccv-2013-Tracking Revisited Using RGBD Camera: Unified Benchmark and Baselines

425 iccv-2013-Tracking via Robust Multi-task Multi-view Joint Sparse Representation

426 iccv-2013-Training Deformable Part Models with Decorrelated Features

427 iccv-2013-Transfer Feature Learning with Joint Distribution Adaptation

428 iccv-2013-Translating Video Content to Natural Language Descriptions

429 iccv-2013-Tree Shape Priors with Connectivity Constraints Using Convex Relaxation on General Graphs

430 iccv-2013-Two-Point Gait: Decoupling Gait from Body Shape

431 iccv-2013-Unbiased Metric Learning: On the Utilization of Multiple Datasets and Web Images for Softening Bias

432 iccv-2013-Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration

433 iccv-2013-Understanding High-Level Semantics by Modeling Traffic Patterns

434 iccv-2013-Unifying Nuclear Norm and Bilinear Factorization Approaches for Low-Rank Matrix Decomposition

435 iccv-2013-Unsupervised Domain Adaptation by Domain Invariant Projection

436 iccv-2013-Unsupervised Intrinsic Calibration from a Single Frame Using a "Plumb-Line" Approach

437 iccv-2013-Unsupervised Random Forest Manifold Alignment for Lipreading

438 iccv-2013-Unsupervised Visual Domain Adaptation Using Subspace Alignment

439 iccv-2013-Video Co-segmentation for Meaningful Action Extraction

440 iccv-2013-Video Event Understanding Using Natural Language Descriptions

441 iccv-2013-Video Motion for Every Visible Point

442 iccv-2013-Video Segmentation by Tracking Many Figure-Ground Segments

443 iccv-2013-Video Synopsis by Heterogeneous Multi-source Correlation

444 iccv-2013-Viewing Real-World Faces in 3D

445 iccv-2013-Visual Reranking through Weakly Supervised Multi-graph Learning

446 iccv-2013-Visual Semantic Complex Network for Web Images

447 iccv-2013-Volumetric Semantic Segmentation Using Pyramid Context Features

448 iccv-2013-Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria

449 iccv-2013-What Do You Do? Occupation Recognition in a Photo via Social Context

450 iccv-2013-What is the Most EfficientWay to Select Nearest Neighbor Candidates for Fast Approximate Nearest Neighbor Search?

451 iccv-2013-Write a Classifier: Zero-Shot Learning Using Purely Textual Descriptions

452 iccv-2013-YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition