title stringlengths 6 154 | authors stringlengths 5 1.96k | abstract stringlengths 392 2.86k ⌀ | pdf_path stringlengths 40 155 | bibtex stringlengths 213 2.79k | download_url stringlengths 87 201 |
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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. Using unlabeled video containing various human activities, the system first learns how body pose tends to change locally in time. Then, given a small number of ... | 2013/Chen_Watching_Unlabeled_Video_2013_CVPR_paper.pdf | @InProceedings{Chen_2013_ICCV_Workshops,author = {Chen, Chao-Yeh and Grauman, Kristen},title = {Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Chen_Watching_Unlabeled_Video_2013_CVPR_paper.pdf |
Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery | Rikke Gade, Anders Jorgensen, Thomas B. Moeslund | This paper presents a robust occupancy analysis system for thermal imaging. Reliable detection of people is very hard in crowded scenes, due to occlusions and segmentation problems. We therefore propose a framework that optimises the occupancy analysis over long periods by including information on the transition in occ... | 2013/Gade_Long-Term_Occupancy_Analysis_2013_CVPR_paper.pdf | @InProceedings{Gade_2013_ICCV_Workshops,author = {Gade, Rikke and Jorgensen, Anders and Moeslund, Thomas B.},title = {Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Gade_Long-Term_Occupancy_Analysis_2013_CVPR_paper.pdf |
Keypoints from Symmetries by Wave Propagation | Samuele Salti, Alessandro Lanza, Luigi Di Stefano | The paper conjectures and demonstrates that repeatable keypoints based on salient symmetries at different scales can be detected by a novel analysis grounded on the wave equation rather than the heat equation underlying traditional Gaussian scale-space theory. While the image structures found by most state-of-the-art d... | 2013/Salti_Keypoints_from_Symmetries_2013_CVPR_paper.pdf | @InProceedings{Salti_2013_ICCV_Workshops,author = {Salti, Samuele and Lanza, Alessandro and Di Stefano, Luigi},title = {Keypoints from Symmetries by Wave Propagation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Salti_Keypoints_from_Symmetries_2013_CVPR_paper.pdf |
Topical Video Object Discovery from Key Frames by Modeling Word Co-occurrence Prior | Gangqiang Zhao, Junsong Yuan, Gang Hua | A topical video object refers to an object that is frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. 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. Pre... | 2013/Zhao_Topical_Video_Object_2013_CVPR_paper.pdf | @InProceedings{Zhao_2013_ICCV_Workshops,author = {Zhao, Gangqiang and Yuan, Junsong and Hua, Gang},title = {Topical Video Object Discovery from Key Frames by Modeling Word Co-occurrence Prior},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhao_Topical_Video_Object_2013_CVPR_paper.pdf |
Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities | Horst Possegger, Sabine Sternig, Thomas Mauthner, Peter M. Roth, Horst Bischof | Combining foreground images from multiple views by projecting them onto a common ground-plane has been recently applied within many multi-object tracking approaches. These planar projections introduce severe artifacts and constrain most approaches to objects moving on a common 2D ground-plane. To overcome these limitat... | 2013/Possegger_Robust_Real-Time_Tracking_2013_CVPR_paper.pdf | @InProceedings{Possegger_2013_ICCV_Workshops,author = {Possegger, Horst and Sternig, Sabine and Mauthner, Thomas and Roth, Peter M. and Bischof, Horst},title = {Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Reco... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Possegger_Robust_Real-Time_Tracking_2013_CVPR_paper.pdf |
Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution | Li He, Hairong Qi, Russell Zaretzki | This paper addresses the problem of learning overcomplete dictionaries for the coupled feature spaces, where the learned dictionaries also reflect the relationship between the two spaces. A Bayesian method using a beta process prior is applied to learn the over-complete dictionaries. Compared to previous couple feature... | 2013/He_Beta_Process_Joint_2013_CVPR_paper.pdf | @InProceedings{He_2013_ICCV_Workshops,author = {He, Li and Qi, Hairong and Zaretzki, Russell},title = {Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},m... | https://openaccess.thecvf.com/content_cvpr_2013/papers/He_Beta_Process_Joint_2013_CVPR_paper.pdf |
A Divide-and-Conquer Method for Scalable Low-Rank Latent Matrix Pursuit | Yan Pan, Hanjiang Lai, Cong Liu, Shuicheng Yan | Data fusion, which effectively fuses multiple prediction lists from different kinds of features to obtain an accurate model, is a crucial component in various computer vision applications. Robust late fusion (RLF) is a recent proposed method that fuses multiple output score lists from different models via pursuing a sh... | 2013/Pan_A_Divide-and-Conquer_Method_2013_CVPR_paper.pdf | @InProceedings{Pan_2013_ICCV_Workshops,author = {Pan, Yan and Lai, Hanjiang and Liu, Cong and Yan, Shuicheng},title = {A Divide-and-Conquer Method for Scalable Low-Rank Latent Matrix Pursuit},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Pan_A_Divide-and-Conquer_Method_2013_CVPR_paper.pdf |
PDM-ENLOR: Learning Ensemble of Local PDM-Based Regressions | Yen H. Le, Uday Kurkure, Ioannis A. Kakadiaris | Statistical shape models, such as Active Shape Models (ASMs), suffer from their inability to represent a large range of variations of a complex shape and to account for the large errors in detection of model points. We propose a novel method (dubbed PDM-ENLOR) that overcomes these limitations by locating each shape mod... | 2013/Le_PDM-ENLOR_Learning_Ensemble_2013_CVPR_paper.pdf | @InProceedings{Le_2013_ICCV_Workshops,author = {Le, Yen H. and Kurkure, Uday and Kakadiaris, Ioannis A.},title = {PDM-ENLOR: Learning Ensemble of Local PDM-Based Regressions},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Le_PDM-ENLOR_Learning_Ensemble_2013_CVPR_paper.pdf |
Fast Trust Region for Segmentation | Lena Gorelick, Frank R. Schmidt, Yuri Boykov | Trust region is a well-known general iterative approach to optimization which offers many advantages over standard gradient descent techniques. In particular, it allows more accurate nonlinear approximation models. In each iteration this approach computes a global optimum of a suitable approximation model within a fixe... | 2013/Gorelick_Fast_Trust_Region_2013_CVPR_paper.pdf | @InProceedings{Gorelick_2013_ICCV_Workshops,author = {Gorelick, Lena and Schmidt, Frank R. and Boykov, Yuri},title = {Fast Trust Region for Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Gorelick_Fast_Trust_Region_2013_CVPR_paper.pdf |
Area Preserving Brain Mapping | Zhengyu Su, Wei Zeng, Rui Shi, Yalin Wang, Jian Sun, Xianfeng Gu | Brain mapping transforms the brain cortical surface to canonical planar domains, which plays a fundamental role in morphological study. Most existing brain mapping methods are based on angle preserving maps, which may introduce large area distortions. This work proposes an area preserving brain mapping method based on ... | 2013/Su_Area_Preserving_Brain_2013_CVPR_paper.pdf | @InProceedings{Su_2013_ICCV_Workshops,author = {Su, Zhengyu and Zeng, Wei and Shi, Rui and Wang, Yalin and Sun, Jian and Gu, Xianfeng},title = {Area Preserving Brain Mapping},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Su_Area_Preserving_Brain_2013_CVPR_paper.pdf |
Multi-level Discriminative Dictionary Learning towards Hierarchical Visual Categorization | Li Shen, Shuhui Wang, Gang Sun, Shuqiang Jiang, Qingming Huang | For the task of visual categorization, the learning model is expected to be endowed with discriminative visual feature representation and flexibilities in processing many categories. Many existing approaches are designed based on a flat category structure, or rely on a set of pre-computed visual features, hence may not... | 2013/Shen_Multi-level_Discriminative_Dictionary_2013_CVPR_paper.pdf | @InProceedings{Shen_2013_ICCV_Workshops,author = {Shen, Li and Wang, Shuhui and Sun, Gang and Jiang, Shuqiang and Huang, Qingming},title = {Multi-level Discriminative Dictionary Learning towards Hierarchical Visual Categorization},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognitio... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Shen_Multi-level_Discriminative_Dictionary_2013_CVPR_paper.pdf |
BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification | Takumi Kobayashi | Image classification methods have been significantly developed in the last decade. Most methods stem from bagof-features (BoF) approach and it is recently extended to a vector aggregation model, such as using Fisher kernels. In this paper, we propose a novel feature extraction method for image classification. Following... | 2013/Kobayashi_BFO_Meets_HOG_2013_CVPR_paper.pdf | @InProceedings{Kobayashi_2013_ICCV_Workshops,author = {Kobayashi, Takumi},title = {BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Kobayashi_BFO_Meets_HOG_2013_CVPR_paper.pdf |
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 | Single-sample face recognition is one of the most challenging problems in face recognition. We propose a novel face recognition algorithm to address this problem based on a sparse representation based classification (SRC) framework. The new algorithm is robust to image misalignment and pixel corruption, and is able to ... | 2013/Zhuang_Single-Sample_Face_Recognition_2013_CVPR_paper.pdf | @InProceedings{Zhuang_2013_ICCV_Workshops,author = {Zhuang, Liansheng and Yang, Allen Y. and Zhou, Zihan and Shankar Sastry, S. and Ma, Yi},title = {Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer},booktitle = {Proceedings of the IEEE Conference on Computer Vision ... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhuang_Single-Sample_Face_Recognition_2013_CVPR_paper.pdf |
GeoF: Geodesic Forests for Learning Coupled Predictors | Peter Kontschieder, Pushmeet Kohli, Jamie Shotton, Antonio Criminisi | Conventional decision forest based methods for image labelling tasks like object segmentation make predictions for each variable (pixel) independently [3, 5, 8]. This prevents them from enforcing dependencies between variables and translates into locally inconsistent pixel labellings. Random field models, instead, enco... | 2013/Kontschieder_GeoF_Geodesic_Forests_2013_CVPR_paper.pdf | @InProceedings{Kontschieder_2013_ICCV_Workshops,author = {Kontschieder, Peter and Kohli, Pushmeet and Shotton, Jamie and Criminisi, Antonio},title = {GeoF: Geodesic Forests for Learning Coupled Predictors},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Kontschieder_GeoF_Geodesic_Forests_2013_CVPR_paper.pdf |
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. This is achieved by solving two major problems encountered by current sampling based algorithms. The first is that the range in which the foreground and background are sampled is often li... | 2013/Shahrian_Improving_Image_Matting_2013_CVPR_paper.pdf | @InProceedings{Shahrian_2013_ICCV_Workshops,author = {Shahrian, Ehsan and Rajan, Deepu and Price, Brian and Cohen, Scott},title = {Improving Image Matting Using Comprehensive Sampling Sets},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Shahrian_Improving_Image_Matting_2013_CVPR_paper.pdf |
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. Our features, called sketch tokens, are learned using supervised mid-level information in the form of hand drawn contours in images. Patches of human generated contours are clustered to form sketch tok... | 2013/Lim_Sketch_Tokens_A_2013_CVPR_paper.pdf | @InProceedings{Lim_2013_ICCV_Workshops,author = {Lim, Joseph J. and Zitnick, C. L. and Dollar, Piotr},title = {Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {201... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lim_Sketch_Tokens_A_2013_CVPR_paper.pdf |
Subspace Interpolation via Dictionary Learning for Unsupervised Domain Adaptation | Jie Ni, Qiang Qiu, Rama Chellappa | Domain adaptation addresses the problem where data instances of a source domain have different distributions from that of a target domain, which occurs frequently in many real life scenarios. This work focuses on unsupervised domain adaptation, where labeled data are only available in the source domain. We propose to i... | 2013/Ni_Subspace_Interpolation_via_2013_CVPR_paper.pdf | @InProceedings{Ni_2013_ICCV_Workshops,author = {Ni, Jie and Qiu, Qiang and Chellappa, Rama},title = {Subspace Interpolation via Dictionary Learning for Unsupervised Domain Adaptation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ni_Subspace_Interpolation_via_2013_CVPR_paper.pdf |
Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation | Luming Zhang, Mingli Song, Zicheng Liu, Xiao Liu, Jiajun Bu, Chun Chen | Weakly supervised image segmentation is a challenging problem in computer vision field. 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. Specifically, we first extract graphlets from each image wh... | 2013/Zhang_Probabilistic_Graphlet_Cut_2013_CVPR_paper.pdf | @InProceedings{Zhang_2013_ICCV_Workshops,author = {Zhang, Luming and Song, Mingli and Liu, Zicheng and Liu, Xiao and Bu, Jiajun and Chen, Chun},title = {Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Visi... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhang_Probabilistic_Graphlet_Cut_2013_CVPR_paper.pdf |
Learning Binary Codes for High-Dimensional Data Using Bilinear Projections | Yunchao Gong, Sanjiv Kumar, Henry A. Rowley, Svetlana Lazebnik | Recent advances in visual recognition indicate that to achieve good retrieval and classification accuracy on largescale datasets like ImageNet, extremely high-dimensional visual descriptors, e.g., Fisher Vectors, are needed. We present a novel method for converting such descriptors to compact similarity-preserving bina... | 2013/Gong_Learning_Binary_Codes_2013_CVPR_paper.pdf | @InProceedings{Gong_2013_ICCV_Workshops,author = {Gong, Yunchao and Kumar, Sanjiv and Rowley, Henry A. and Lazebnik, Svetlana},title = {Learning Binary Codes for High-Dimensional Data Using Bilinear Projections},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Gong_Learning_Binary_Codes_2013_CVPR_paper.pdf |
Fast Energy Minimization Using Learned State Filters | Matthieu Guillaumin, Luc Van Gool, Vittorio Ferrari | Pairwise discrete energies defined over graphs are ubiquitous in computer vision. Many algorithms have been proposed to minimize such energies, often concentrating on sparse graph topologies or specialized classes of pairwise potentials. However, when the graph is fully connected and the pairwise potentials are arbitra... | 2013/Guillaumin_Fast_Energy_Minimization_2013_CVPR_paper.pdf | @InProceedings{Guillaumin_2013_ICCV_Workshops,author = {Guillaumin, Matthieu and Van Gool, Luc and Ferrari, Vittorio},title = {Fast Energy Minimization Using Learned State Filters},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Guillaumin_Fast_Energy_Minimization_2013_CVPR_paper.pdf |
Saliency Aggregation: A Data-Driven Approach | Long Mai, Yuzhen Niu, Feng Liu | A variety of methods have been developed for visual saliency analysis. These methods often complement each other. This paper addresses the problem of aggregating various saliency analysis methods such that the aggregation result outperforms each individual one. We have two major observations. First, different methods p... | 2013/Mai_Saliency_Aggregation_A_2013_CVPR_paper.pdf | @InProceedings{Mai_2013_ICCV_Workshops,author = {Mai, Long and Niu, Yuzhen and Liu, Feng},title = {Saliency Aggregation: A Data-Driven Approach},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Mai_Saliency_Aggregation_A_2013_CVPR_paper.pdf |
Multi-scale Curve Detection on Surfaces | Michael Kolomenkin, Ilan Shimshoni, Ayellet Tal | This paper extends to surfaces the multi-scale approach of edge detection on images. The common practice for detecting curves on surfaces requires the user to first select the scale of the features, apply an appropriate smoothing, and detect the edges on the smoothed surface. This approach suffers from two drawbacks. F... | 2013/Kolomenkin_Multi-scale_Curve_Detection_2013_CVPR_paper.pdf | @InProceedings{Kolomenkin_2013_ICCV_Workshops,author = {Kolomenkin, Michael and Shimshoni, Ilan and Tal, Ayellet},title = {Multi-scale Curve Detection on Surfaces},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Kolomenkin_Multi-scale_Curve_Detection_2013_CVPR_paper.pdf |
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. Through a line sampling process, the video is first converted into a temporal slice image. Next, the number of people is estimated in a set of overlapping sliding windows on th... | 2013/Ma_Crossing_the_Line_2013_CVPR_paper.pdf | @InProceedings{Ma_2013_ICCV_Workshops,author = {Ma, Zheng and Chan, Antoni B.},title = {Crossing the Line: Crowd Counting by Integer Programming with Local Features},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ma_Crossing_the_Line_2013_CVPR_paper.pdf |
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). DiSC solves the subspace clustering problem by using a quadratic classifier trained from unlabeled data (clustering by classification). We generate labels by exploiting ... | 2013/Zografos_Discriminative_Subspace_Clustering_2013_CVPR_paper.pdf | @InProceedings{Zografos_2013_ICCV_Workshops,author = {Zografos, Vasileios and Ellis, Liam and Mester, Rudolf},title = {Discriminative Subspace Clustering},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zografos_Discriminative_Subspace_Clustering_2013_CVPR_paper.pdf |
Measuring Crowd Collectiveness | Bolei Zhou, Xiaoou Tang, Xiaogang Wang | Collective motions are common in crowd systems and have attracted a great deal of attention in a variety of multidisciplinary fields. Collectiveness, which indicates the degree of individuals acting as a union in collective motion, is a fundamental and universal measurement for various crowd systems. By integrating pat... | 2013/Zhou_Measuring_Crowd_Collectiveness_2013_CVPR_paper.pdf | @InProceedings{Zhou_2013_ICCV_Workshops,author = {Zhou, Bolei and Tang, Xiaoou and Wang, Xiaogang},title = {Measuring Crowd Collectiveness},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhou_Measuring_Crowd_Collectiveness_2013_CVPR_paper.pdf |
Whitened Expectation Propagation: Non-Lambertian Shape from Shading and Shadow | Brian Potetz, Mohammadreza Hajiarbabi | For problems over continuous random variables, MRFs with large cliques pose a challenge in probabilistic inference. Difficulties in performing optimization efficiently have limited the probabilistic models explored in computer vision and other fields. One inference technique that handles large cliques well is Expectati... | 2013/Potetz_Whitened_Expectation_Propagation_2013_CVPR_paper.pdf | @InProceedings{Potetz_2013_ICCV_Workshops,author = {Potetz, Brian and Hajiarbabi, Mohammadreza},title = {Whitened Expectation Propagation: Non-Lambertian Shape from Shading and Shadow},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Potetz_Whitened_Expectation_Propagation_2013_CVPR_paper.pdf |
MKPLS: Manifold Kernel Partial Least Squares for Lipreading and Speaker Identification | Amr Bakry, Ahmed Elgammal | Visual speech recognition is a challenging problem, due to confusion between visual speech features. The speaker identification problem is usually coupled with speech recognition. Moreover, speaker identification is important to several applications, such as automatic access control, biometrics, authentication, and per... | 2013/Bakry_MKPLS_Manifold_Kernel_2013_CVPR_paper.pdf | @InProceedings{Bakry_2013_ICCV_Workshops,author = {Bakry, Amr and Elgammal, Ahmed},title = {MKPLS: Manifold Kernel Partial Least Squares for Lipreading and Speaker Identification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Bakry_MKPLS_Manifold_Kernel_2013_CVPR_paper.pdf |
Multi-class Video Co-segmentation with a Generative Multi-video Model | Wei-Chen Chiu, Mario Fritz | Video data provides a rich source of information that is available to us today in large quantities e.g. from online resources. Tasks like segmentation benefit greatly from the analysis of spatio-temporal motion patterns in videos and recent advances in video segmentation has shown great progress in exploiting these add... | 2013/Chiu_Multi-class_Video_Co-segmentation_2013_CVPR_paper.pdf | @InProceedings{Chiu_2013_ICCV_Workshops,author = {Chiu, Wei-Chen and Fritz, Mario},title = {Multi-class Video Co-segmentation with a Generative Multi-video Model},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Chiu_Multi-class_Video_Co-segmentation_2013_CVPR_paper.pdf |
Lp-Norm IDF for Large Scale Image Search | Liang Zheng, Shengjin Wang, Ziqiong Liu, Qi Tian | The Inverse Document Frequency (IDF) is prevalently utilized in the Bag-of-Words based image search. The basic idea is to assign less weight to terms with high frequency, and vice versa. However, the estimation of visual word frequency is coarse and heuristic. Therefore, the effectiveness of the conventional IDF routin... | 2013/Zheng_Lp-Norm_IDF_for_2013_CVPR_paper.pdf | @InProceedings{Zheng_2013_ICCV_Workshops,author = {Zheng, Liang and Wang, Shengjin and Liu, Ziqiong and Tian, Qi},title = {Lp-Norm IDF for Large Scale Image Search},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zheng_Lp-Norm_IDF_for_2013_CVPR_paper.pdf |
Saliency Detection via Graph-Based Manifold Ranking | Chuan Yang, Lihe Zhang, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang | Most existing bottom-up methods measure the foreground saliency of a pixel or region based on its contrast within a local context or the entire image, whereas a few methods focus on segmenting out background regions and thereby salient objects. Instead of considering the contrast between the salient objects and their s... | 2013/Yang_Saliency_Detection_via_2013_CVPR_paper.pdf | @InProceedings{Yang_2013_ICCV_Workshops,author = {Yang, Chuan and Zhang, Lihe and Lu, Huchuan and Ruan, Xiang and Yang, Ming-Hsuan},title = {Saliency Detection via Graph-Based Manifold Ranking},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yang_Saliency_Detection_via_2013_CVPR_paper.pdf |
Online Object Tracking: A Benchmark | Yi Wu, Jongwoo Lim, Ming-Hsuan Yang | Object tracking is one of the most important components in numerous applications of computer vision. While much progress has been made in recent years with efforts on sharing code and datasets, it is of great importance to develop a library and benchmark to gauge the state of the art. After briefly reviewing recent adv... | 2013/Wu_Online_Object_Tracking_2013_CVPR_paper.pdf | @InProceedings{Wu_2013_ICCV_Workshops,author = {Wu, Yi and Lim, Jongwoo and Yang, Ming-Hsuan},title = {Online Object Tracking: A Benchmark},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wu_Online_Object_Tracking_2013_CVPR_paper.pdf |
Tracking Sports Players with Context-Conditioned Motion Models | Jingchen Liu, Peter Carr, Robert T. Collins, Yanxi Liu | We employ hierarchical data association to track players in team sports. Player movements are often complex and highly correlated with both nearby and distant players. A single model would require many degrees of freedom to represent the full motion diversity and could be difficult to use in practice. Instead, we intro... | 2013/Liu_Tracking_Sports_Players_2013_CVPR_paper.pdf | @InProceedings{Liu_2013_ICCV_Workshops,author = {Liu, Jingchen and Carr, Peter and Collins, Robert T. and Liu, Yanxi},title = {Tracking Sports Players with Context-Conditioned Motion Models},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Liu_Tracking_Sports_Players_2013_CVPR_paper.pdf |
Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces | Shaokang Chen, Conrad Sanderson, Mehrtash T. Harandi, Brian C. Lovell | Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different u... | 2013/Chen_Improved_Image_Set_2013_CVPR_paper.pdf | @InProceedings{Chen_2013_ICCV_Workshops,author = {Chen, Shaokang and Sanderson, Conrad and Harandi, Mehrtash T. and Lovell, Brian C.},title = {Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CV... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Chen_Improved_Image_Set_2013_CVPR_paper.pdf |
Underwater Camera Calibration Using Wavelength Triangulation | Timothy Yau, Minglun Gong, Yee-Hong Yang | In underwater imagery, the image formation process includes refractions that occur when light passes from water into the camera housing, typically through a flat glass port. We extend the existing work on physical refraction models by considering the dispersion of light, and derive new constraints on the model paramete... | 2013/Yau_Underwater_Camera_Calibration_2013_CVPR_paper.pdf | @InProceedings{Yau_2013_ICCV_Workshops,author = {Yau, Timothy and Gong, Minglun and Yang, Yee-Hong},title = {Underwater Camera Calibration Using Wavelength Triangulation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yau_Underwater_Camera_Calibration_2013_CVPR_paper.pdf |
Physically Plausible 3D Scene Tracking: The Single Actor Hypothesis | Nikolaos Kyriazis, Antonis Argyros | In several hand-object(s) interaction scenarios, the change in the objects' state is a direct consequence of the hand's motion. This has a straightforward representation in Newtonian dynamics. We present the first approach that exploits this observation to perform model-based 3D tracking of a table-top scene comprising... | 2013/Kyriazis_Physically_Plausible_3D_2013_CVPR_paper.pdf | @InProceedings{Kyriazis_2013_ICCV_Workshops,author = {Kyriazis, Nikolaos and Argyros, Antonis},title = {Physically Plausible 3D Scene Tracking: The Single Actor Hypothesis},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Kyriazis_Physically_Plausible_3D_2013_CVPR_paper.pdf |
Joint Sparsity-Based Representation and Analysis of Unconstrained Activities | Raghuraman Gopalan | While the notion of joint sparsity in understanding common and innovative components of a multi-receiver signal ensemble has been well studied, we investigate the utility of such joint sparse models in representing information contained in a single video signal. By decomposing the content of a video sequence into that ... | 2013/Gopalan_Joint_Sparsity-Based_Representation_2013_CVPR_paper.pdf | @InProceedings{Gopalan_2013_ICCV_Workshops,author = {Gopalan, Raghuraman},title = {Joint Sparsity-Based Representation and Analysis of Unconstrained Activities},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Gopalan_Joint_Sparsity-Based_Representation_2013_CVPR_paper.pdf |
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. The face is modeled using an active appearance model (AAM), and several extensions are prop... | 2013/Anderson_Expressive_Visual_Text-to-Speech_2013_CVPR_paper.pdf | @InProceedings{Anderson_2013_ICCV_Workshops,author = {Anderson, Robert and Stenger, Bjorn and Wan, Vincent and Cipolla, Roberto},title = {Expressive Visual Text-to-Speech Using Active Appearance Models},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},yea... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Anderson_Expressive_Visual_Text-to-Speech_2013_CVPR_paper.pdf |
Robust Monocular Epipolar Flow Estimation | Koichiro Yamaguchi, David McAllester, Raquel Urtasun | We consider the problem of computing optical flow in monocular video taken from a moving vehicle. In this setting, the vast majority of image flow is due to the vehicle's ego-motion. We propose to take advantage of this fact and estimate flow along the epipolar lines of the egomotion. Towards this goal, we derive a sla... | 2013/Yamaguchi_Robust_Monocular_Epipolar_2013_CVPR_paper.pdf | @InProceedings{Yamaguchi_2013_ICCV_Workshops,author = {Yamaguchi, Koichiro and McAllester, David and Urtasun, Raquel},title = {Robust Monocular Epipolar Flow Estimation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yamaguchi_Robust_Monocular_Epipolar_2013_CVPR_paper.pdf |
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 | Analyzing brain networks from neuroimages is becoming a promising approach in identifying novel connectivitybased biomarkers for the Alzheimer's disease (AD). In this regard, brain "effective connectivity" analysis, which studies the causal relationship among brain regions, is highly challenging and of many research op... | 2013/Zhou_Discriminative_Brain_Effective_2013_CVPR_paper.pdf | @InProceedings{Zhou_2013_ICCV_Workshops,author = {Zhou, Luping and Wang, Lei and Liu, Lingqiao and Ogunbona, Philip and Shen, Dinggang},title = {Discriminative Brain Effective Connectivity Analysis for Alzheimer's Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network},booktitle = {Proceedings of the... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhou_Discriminative_Brain_Effective_2013_CVPR_paper.pdf |
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine | Hua Wang, Feiping Nie, Heng Huang, Chris Ding | To better understand, search, and classify image and video information, many visual feature descriptors have been proposed to describe elementary visual characteristics, such as the shape, the color, the texture, etc. How to integrate these heterogeneous visual features and identify the important ones from them for spe... | 2013/Wang_Heterogeneous_Visual_Features_2013_CVPR_paper.pdf | @InProceedings{Wang_2013_ICCV_Workshops,author = {Wang, Hua and Nie, Feiping and Huang, Heng and Ding, Chris},title = {Heterogeneous Visual Features Fusion via Sparse Multimodal Machine},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wang_Heterogeneous_Visual_Features_2013_CVPR_paper.pdf |
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. Dominant behaviors are those occurring frequently in videos and hence, usually do not attract much attention. They can be characterized by different complexities in space and time, ... | 2013/Roshtkhari_Online_Dominant_and_2013_CVPR_paper.pdf | @InProceedings{Roshtkhari_2013_ICCV_Workshops,author = {Javan Roshtkhari, Mehrsan and Levine, Martin D.},title = {Online Dominant and Anomalous Behavior Detection in Videos},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Roshtkhari_Online_Dominant_and_2013_CVPR_paper.pdf |
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 | The problem of describing images through natural language has gained importance in the computer vision community. Solutions to image description have either focused on a top-down approach of generating language through combinations of object detections and language models or bottom-up propagation of keyword tags from t... | 2013/Das_A_Thousand_Frames_2013_CVPR_paper.pdf | @InProceedings{Das_2013_ICCV_Workshops,author = {Das, Pradipto and Xu, Chenliang and Doell, Richard F. and Corso, Jason J.},title = {A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching},booktitle = {Proceedings of the IEEE Conference on Computer Vision ... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Das_A_Thousand_Frames_2013_CVPR_paper.pdf |
Spectral Modeling and Relighting of Reflective-Fluorescent Scenes | Antony Lam, Imari Sato | Hyperspectral reflectance data allows for highly accurate spectral relighting under arbitrary illumination, which is invaluable to applications ranging from archiving cultural e-heritage to consumer product design. Past methods for capturing the spectral reflectance of scenes has proven successful in relighting but the... | 2013/Lam_Spectral_Modeling_and_2013_CVPR_paper.pdf | @InProceedings{Lam_2013_ICCV_Workshops,author = {Lam, Antony and Sato, Imari},title = {Spectral Modeling and Relighting of Reflective-Fluorescent Scenes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lam_Spectral_Modeling_and_2013_CVPR_paper.pdf |
Is There a Procedural Logic to Architecture? | Julien Weissenberg, Hayko Riemenschneider, Mukta Prasad, Luc Van Gool | Urban models are key to navigation, architecture and entertainment. Apart from visualizing fac,ades, a number of tedious tasks remain largely manual (e.g. compression, generating new fac,ade designs and structurally comparing fac,ades for classification, retrieval and clustering). We propose a novel procedural modellin... | 2013/Weissenberg_Is_There_a_2013_CVPR_paper.pdf | @InProceedings{Weissenberg_2013_ICCV_Workshops,author = {Weissenberg, Julien and Riemenschneider, Hayko and Prasad, Mukta and Van Gool, Luc},title = {Is There a Procedural Logic to Architecture?},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {20... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Weissenberg_Is_There_a_2013_CVPR_paper.pdf |
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. The set of objects in training images for an image class are treated as a collage. When presented with a test image, the best matching between this collage of training image objects and those in the test image is found. ... | 2013/Zhou_Learning_Class-to-Image_Distance_2013_CVPR_paper.pdf | @InProceedings{Zhou_2013_ICCV_Workshops,author = {Zhou, Guang-Tong and Lan, Tian and Yang, Weilong and Mori, Greg},title = {Learning Class-to-Image Distance with Object Matchings},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhou_Learning_Class-to-Image_Distance_2013_CVPR_paper.pdf |
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. By modeling the multicamera system as a generalized camera and applying the non-holonomic motion constraint of a car, we show that this leads to a novel 2-point minimal solution ... | 2013/Lee_Motion_Estimation_for_2013_CVPR_paper.pdf | @InProceedings{Lee_2013_ICCV_Workshops,author = {Hee Lee, Gim and Faundorfer, Friedrich and Pollefeys, Marc},title = {Motion Estimation for Self-Driving Cars with a Generalized Camera},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lee_Motion_Estimation_for_2013_CVPR_paper.pdf |
Histograms of Sparse Codes for Object Detection | Xiaofeng Ren, Deva Ramanan | Object detection has seen huge progress in recent years, much thanks to the heavily-engineered Histograms of Oriented Gradients (HOG) features. Can we go beyond gradients and do better than HOG? We provide an affirmative answer by proposing and investigating a sparse representation for object detection, Histograms of S... | 2013/Ren_Histograms_of_Sparse_2013_CVPR_paper.pdf | @InProceedings{Ren_2013_ICCV_Workshops,author = {Ren, Xiaofeng and Ramanan, Deva},title = {Histograms of Sparse Codes for Object Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ren_Histograms_of_Sparse_2013_CVPR_paper.pdf |
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. The extracted primary object regions are then used to build object models for optimized video segmentation. The proposed approach has several contributions: First, a novel layered Directed Acyclic Gr... | 2013/Zhang_Video_Object_Segmentation_2013_CVPR_paper.pdf | @InProceedings{Zhang_2013_ICCV_Workshops,author = {Zhang, Dong and Javed, Omar and Shah, Mubarak},title = {Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mo... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhang_Video_Object_Segmentation_2013_CVPR_paper.pdf |
Capturing Complex Spatio-temporal Relations among Facial Muscles for Facial Expression Recognition | Ziheng Wang, Shangfei Wang, Qiang Ji | Spatial-temporal relations among facial muscles carry crucial information about facial expressions yet have not been thoroughly exploited. One contributing factor for this is the limited ability of the current dynamic models in capturing complex spatial and temporal relations. Existing dynamic models can only capture s... | 2013/Wang_Capturing_Complex_Spatio-temporal_2013_CVPR_paper.pdf | @InProceedings{Wang_2013_ICCV_Workshops,author = {Wang, Ziheng and Wang, Shangfei and Ji, Qiang},title = {Capturing Complex Spatio-temporal Relations among Facial Muscles for Facial Expression Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wang_Capturing_Complex_Spatio-temporal_2013_CVPR_paper.pdf |
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. DFD suffers from important limitations namely coarse shape reconstruction and poor accuracy on textureless surfaces that can be overcome with the help of shading. We integrate both forms of data within ... | 2013/Li_Bayesian_Depth-from-Defocus_with_2013_CVPR_paper.pdf | @InProceedings{Li_2013_ICCV_Workshops,author = {Li, Chen and Su, Shuochen and Matsushita, Yasuyuki and Zhou, Kun and Lin, Stephen},title = {Bayesian Depth-from-Defocus with Shading Constraints},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Li_Bayesian_Depth-from-Defocus_with_2013_CVPR_paper.pdf |
Boundary Cues for 3D Object Shape Recovery | Kevin Karsch, Zicheng Liao, Jason Rock, Jonathan T. Barron, Derek Hoiem | Early work in computer vision considered a host of geometric cues for both shape reconstruction [11] and recognition [14]. However, since then, the vision community has focused heavily on shading cues for reconstruction [1], and moved towards data-driven approaches for recognition [6]. In this paper, we reconsider thes... | 2013/Karsch_Boundary_Cues_for_2013_CVPR_paper.pdf | @InProceedings{Karsch_2013_ICCV_Workshops,author = {Karsch, Kevin and Liao, Zicheng and Rock, Jason and Barron, Jonathan T. and Hoiem, Derek},title = {Boundary Cues for 3D Object Shape Recovery},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {201... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Karsch_Boundary_Cues_for_2013_CVPR_paper.pdf |
Sparse Output Coding for Large-Scale Visual Recognition | Bin Zhao, Eric P. Xing | Many vision tasks require a multi-class classifier to discriminate multiple categories, on the order of hundreds or thousands. 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 pr... | 2013/Zhao_Sparse_Output_Coding_2013_CVPR_paper.pdf | @InProceedings{Zhao_2013_ICCV_Workshops,author = {Zhao, Bin and Xing, Eric P.},title = {Sparse Output Coding for Large-Scale Visual Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Zhao_Sparse_Output_Coding_2013_CVPR_paper.pdf |
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. This approach allows the weights of region and boundary features to adapt to the segmentation scale at which they are applied. The stages of the cascade ar... | 2013/Ren_Image_Segmentation_by_2013_CVPR_paper.pdf | @InProceedings{Ren_2013_ICCV_Workshops,author = {Ren, Zhile and Shakhnarovich, Gregory},title = {Image Segmentation by Cascaded Region Agglomeration},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ren_Image_Segmentation_by_2013_CVPR_paper.pdf |
Can a Fully Unconstrained Imaging Model Be Applied Effectively to Central Cameras? | Filippo Bergamasco, Andrea Albarelli, Emanuele Rodola, Andrea Torsello | Traditional camera models are often the result of a compromise between the ability to account for non-linearities in the image formation model and the need for a feasible number of degrees of freedom in the estimation process. These considerations led to the definition of several ad hoc models that best adapt to differ... | 2013/Bergamasco_Can_a_Fully_2013_CVPR_paper.pdf | @InProceedings{Bergamasco_2013_ICCV_Workshops,author = {Bergamasco, Filippo and Albarelli, Andrea and Rodola, Emanuele and Torsello, Andrea},title = {Can a Fully Unconstrained Imaging Model Be Applied Effectively to Central Cameras?},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recogni... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Bergamasco_Can_a_Fully_2013_CVPR_paper.pdf |
Spatial Inference Machines | Roman Shapovalov, Dmitry Vetrov, Pushmeet Kohli | This paper addresses the problem of semantic segmentation of 3D point clouds. We extend the inference machines framework of Ross et al. by adding spatial factors that model mid-range and long-range dependencies inherent in the data. The new model is able to account for semantic spatial context. During training, our met... | 2013/Shapovalov_Spatial_Inference_Machines_2013_CVPR_paper.pdf | @InProceedings{Shapovalov_2013_ICCV_Workshops,author = {Shapovalov, Roman and Vetrov, Dmitry and Kohli, Pushmeet},title = {Spatial Inference Machines},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Shapovalov_Spatial_Inference_Machines_2013_CVPR_paper.pdf |
Learning Compact Binary Codes for Visual Tracking | Xi Li, Chunhua Shen, Anthony Dick, Anton van den Hengel | A key problem in visual tracking is to represent the appearance of an object in a way that is robust to visual changes. To attain this robustness, increasingly complex models are used to capture appearance variations. However, such models can be difficult to maintain accurately and efficiently. In this paper, we propos... | 2013/Li_Learning_Compact_Binary_2013_CVPR_paper.pdf | @InProceedings{Li_2013_ICCV_Workshops,author = {Li, Xi and Shen, Chunhua and Dick, Anthony and van den Hengel, Anton},title = {Learning Compact Binary Codes for Visual Tracking},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Li_Learning_Compact_Binary_2013_CVPR_paper.pdf |
Efficient Maximum Appearance Search for Large-Scale Object Detection | Qiang Chen, Zheng Song, Rogerio Feris, Ankur Datta, Liangliang Cao, Zhongyang Huang, Shuicheng Yan | In recent years, efficiency of large-scale object detection has arisen as an important topic due to the exponential growth in the size of benchmark object detection datasets. Most current object detection methods focus on improving accuracy of large-scale object detection with efficiency being an afterthought. In this ... | 2013/Chen_Efficient_Maximum_Appearance_2013_CVPR_paper.pdf | @InProceedings{Chen_2013_ICCV_Workshops,author = {Chen, Qiang and Song, Zheng and Feris, Rogerio and Datta, Ankur and Cao, Liangliang and Huang, Zhongyang and Yan, Shuicheng},title = {Efficient Maximum Appearance Search for Large-Scale Object Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Chen_Efficient_Maximum_Appearance_2013_CVPR_paper.pdf |
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. Our analysis is based on establishing the integrability constraint. In the orthographic projection case, it is well-known that when such constraint is... | 2013/Papadhimitri_A_New_Perspective_2013_CVPR_paper.pdf | @InProceedings{Papadhimitri_2013_ICCV_Workshops,author = {Papadhimitri, Thoma and Favaro, Paolo},title = {A New Perspective on Uncalibrated Photometric Stereo},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Papadhimitri_A_New_Perspective_2013_CVPR_paper.pdf |
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. We learn a set of textons describing the images, and use them to divide the image into super-pixels represented by their texton. We then learn, for each texton, the frequency of generating on-trail... | 2013/Predoehl_A_Statistical_Model_2013_CVPR_paper.pdf | @InProceedings{Predoehl_2013_ICCV_Workshops,author = {Predoehl, Andrew and Morris, Scott and Barnard, Kobus},title = {A Statistical Model for Recreational Trails in Aerial Images},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Predoehl_A_Statistical_Model_2013_CVPR_paper.pdf |
A Joint Model for 2D and 3D Pose Estimation from a Single Image | Edgar Simo-Serra, Ariadna Quattoni, Carme Torras, Francesc Moreno-Noguer | We introduce a novel approach to automatically recover 3D human pose from a single image. Most previous work follows a pipelined approach: initially, a set of 2D features such as edges, joints or silhouettes are detected in the image, and then these observations are used to infer the 3D pose. Solving these two problems... | 2013/Simo-Serra_A_Joint_Model_2013_CVPR_paper.pdf | @InProceedings{Simo-Serra_2013_ICCV_Workshops,author = {Simo-Serra, Edgar and Quattoni, Ariadna and Torras, Carme and Moreno-Noguer, Francesc},title = {A Joint Model for 2D and 3D Pose Estimation from a Single Image},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mont... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Simo-Serra_A_Joint_Model_2013_CVPR_paper.pdf |
Learning Video Saliency from Human Gaze Using Candidate Selection | Dmitry Rudoy, Dan B. Goldman, Eli Shechtman, Lihi Zelnik-Manor | During recent years remarkable progress has been made in visual saliency modeling. Our interest is in video saliency. Since videos are fundamentally different from still images, they are viewed differently by human observers. For example, the time each video frame is observed is a fraction of a second, while a still im... | 2013/Rudoy_Learning_Video_Saliency_2013_CVPR_paper.pdf | @InProceedings{Rudoy_2013_ICCV_Workshops,author = {Rudoy, Dmitry and Goldman, Dan B. and Shechtman, Eli and Zelnik-Manor, Lihi},title = {Learning Video Saliency from Human Gaze Using Candidate Selection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},ye... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Rudoy_Learning_Video_Saliency_2013_CVPR_paper.pdf |
Designing Category-Level Attributes for Discriminative Visual Recognition | Felix X. Yu, Liangliang Cao, Rogerio S. Feris, John R. Smith, Shih-Fu Chang | Attribute-based representation has shown great promises for visual recognition due to its intuitive interpretation and cross-category generalization property. However, human efforts are usually involved in the attribute designing process, making the representation costly to obtain. In this paper, we propose a novel for... | 2013/Yu_Designing_Category-Level_Attributes_2013_CVPR_paper.pdf | @InProceedings{Yu_2013_ICCV_Workshops,author = {Yu, Felix X. and Cao, Liangliang and Feris, Rogerio S. and Smith, John R. and Chang, Shih-Fu},title = {Designing Category-Level Attributes for Discriminative Visual Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CV... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yu_Designing_Category-Level_Attributes_2013_CVPR_paper.pdf |
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. For this, we downplay measurements coming from areas that are unlikely to belong to the same region as the descriptor's center, as suggested by soft segmentation masks. Our treatment is... | 2013/Trulls_Dense_Segmentation-Aware_Descriptors_2013_CVPR_paper.pdf | @InProceedings{Trulls_2013_ICCV_Workshops,author = {Trulls, Eduard and Kokkinos, Iasonas and Sanfeliu, Alberto and Moreno-Noguer, Francesc},title = {Dense Segmentation-Aware Descriptors},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Trulls_Dense_Segmentation-Aware_Descriptors_2013_CVPR_paper.pdf |
Modeling Mutual Visibility Relationship in Pedestrian Detection | Wanli Ouyang, Xingyu Zeng, Xiaogang Wang | Detecting pedestrians in cluttered scenes is a challenging problem in computer vision. The difficulty is added when several pedestrians overlap in images and occlude each other. We observe, however, that the occlusion/visibility statuses of overlapping pedestrians provide useful mutual relationship for visibility estim... | 2013/Ouyang_Modeling_Mutual_Visibility_2013_CVPR_paper.pdf | @InProceedings{Ouyang_2013_ICCV_Workshops,author = {Ouyang, Wanli and Zeng, Xingyu and Wang, Xiaogang},title = {Modeling Mutual Visibility Relationship in Pedestrian Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ouyang_Modeling_Mutual_Visibility_2013_CVPR_paper.pdf |
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. To explore the appearance and geometry space of latent structures effectively, we first quantize the image lattice using an overcomplete set of shape primitives, and then or... | 2013/Song_Discriminatively_Trained_And-Or_2013_CVPR_paper.pdf | @InProceedings{Song_2013_ICCV_Workshops,author = {Song, Xi and Wu, Tianfu and Jia, Yunde and Zhu, Song-Chun},title = {Discriminatively Trained And-Or Tree Models for Object Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Song_Discriminatively_Trained_And-Or_2013_CVPR_paper.pdf |
Cross-View Image Geolocalization | Tsung-Yi Lin, Serge Belongie, James Hays | The recent availability of large amounts of geotagged imagery has inspired a number of data driven solutions to the image geolocalization problem. Existing approaches predict the location of a query image by matching it to a database of georeferenced photographs. While there are many geotagged images available on photo... | 2013/Lin_Cross-View_Image_Geolocalization_2013_CVPR_paper.pdf | @InProceedings{Lin_2013_ICCV_Workshops,author = {Lin, Tsung-Yi and Belongie, Serge and Hays, James},title = {Cross-View Image Geolocalization},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lin_Cross-View_Image_Geolocalization_2013_CVPR_paper.pdf |
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. Though SIRFS performs well on images of segmented objects, it performs poorly on images of natural scenes, which contain occlusion and spatially-varying ill... | 2013/Barron_Intrinsic_Scene_Properties_2013_CVPR_paper.pdf | @InProceedings{Barron_2013_ICCV_Workshops,author = {Barron, Jonathan T. and Malik, Jitendra},title = {Intrinsic Scene Properties from a Single RGB-D Image},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Barron_Intrinsic_Scene_Properties_2013_CVPR_paper.pdf |
Learning Cross-Domain Information Transfer for Location Recognition and Clustering | Raghuraman Gopalan | Estimating geographic location from images is a challenging problem that is receiving recent attention. 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. St... | 2013/Gopalan_Learning_Cross-Domain_Information_2013_CVPR_paper.pdf | @InProceedings{Gopalan_2013_ICCV_Workshops,author = {Gopalan, Raghuraman},title = {Learning Cross-Domain Information Transfer for Location Recognition and Clustering},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Gopalan_Learning_Cross-Domain_Information_2013_CVPR_paper.pdf |
Robust Multi-resolution Pedestrian Detection in Traffic Scenes | Junjie Yan, Xucong Zhang, Zhen Lei, Shengcai Liao, Stan Z. Li | The serious performance decline with decreasing resolution is the major bottleneck for current pedestrian detection techniques [14, 23]. 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 differe... | 2013/Yan_Robust_Multi-resolution_Pedestrian_2013_CVPR_paper.pdf | @InProceedings{Yan_2013_ICCV_Workshops,author = {Yan, Junjie and Zhang, Xucong and Lei, Zhen and Liao, Shengcai and Li, Stan Z.},title = {Robust Multi-resolution Pedestrian Detection in Traffic Scenes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yan_Robust_Multi-resolution_Pedestrian_2013_CVPR_paper.pdf |
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. Rotational-invariant neighborhood-based textural representations are extracted and used to learn a set of representative texture atoms for defining a sparse texture model for the image. Based on t... | 2013/Scharfenberger_Statistical_Textural_Distinctiveness_2013_CVPR_paper.pdf | @InProceedings{Scharfenberger_2013_ICCV_Workshops,author = {Scharfenberger, Christian and Wong, Alexander and Fergani, Khalil and Zelek, John S. and Clausi, David A.},title = {Statistical Textural Distinctiveness for Salient Region Detection in Natural Images},booktitle = {Proceedings of the IEEE Conference on Computer... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Scharfenberger_Statistical_Textural_Distinctiveness_2013_CVPR_paper.pdf |
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. A video sequence is decomposed into short-term segments, which are characterized by the dynamics of their attributes. These segments are modeled by a dictionary of attribute dynamics ... | 2013/Li_Recognizing_Activities_via_2013_CVPR_paper.pdf | @InProceedings{Li_2013_ICCV_Workshops,author = {Li, Weixin and Yu, Qian and Sawhney, Harpreet and Vasconcelos, Nuno},title = {Recognizing Activities via Bag of Words for Attribute Dynamics},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Li_Recognizing_Activities_via_2013_CVPR_paper.pdf |
Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking | Martin Hofmann, Daniel Wolf, Gerhard Rigoll | We generalize the network flow formulation for multiobject tracking to multi-camera setups. In the past, reconstruction of multi-camera data was done as a separate extension. In this work, we present a combined maximum a posteriori (MAP) formulation, which jointly models multicamera reconstruction as well as global tem... | 2013/Hofmann_Hypergraphs_for_Joint_2013_CVPR_paper.pdf | @InProceedings{Hofmann_2013_ICCV_Workshops,author = {Hofmann, Martin and Wolf, Daniel and Rigoll, Gerhard},title = {Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Hofmann_Hypergraphs_for_Joint_2013_CVPR_paper.pdf |
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. The paper characterizes the performance of a simple but effective edge detection scheme which can be computed rapidly and offers performance that is competitive with the pB detector. The paper also... | 2013/Taylor_Towards_Fast_and_2013_CVPR_paper.pdf | @InProceedings{Taylor_2013_ICCV_Workshops,author = {Taylor, Camillo J.},title = {Towards Fast and Accurate Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Taylor_Towards_Fast_and_2013_CVPR_paper.pdf |
Robust Object Co-detection | Xin Guo, Dong Liu, Brendan Jou, Mojun Zhu, Anni Cai, Shih-Fu Chang | Object co-detection aims at simultaneous detection of objects of the same category from a pool of related images by exploiting consistent visual patterns present in candidate objects in the images. The related image set may contain a mixture of annotated objects and candidate objects generated by automatic detectors. C... | 2013/Guo_Robust_Object_Co-detection_2013_CVPR_paper.pdf | @InProceedings{Guo_2013_ICCV_Workshops,author = {Guo, Xin and Liu, Dong and Jou, Brendan and Zhu, Mojun and Cai, Anni and Chang, Shih-Fu},title = {Robust Object Co-detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Guo_Robust_Object_Co-detection_2013_CVPR_paper.pdf |
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 | Many object detection systems are constrained by the time required to convolve a target image with a bank of filters that code for different aspects of an object's appearance, such as the presence of component parts. We exploit locality-sensitive hashing to replace the dot-product kernel operator in the convolution wit... | 2013/Dean_Fast_Accurate_Detection_2013_CVPR_paper.pdf | @InProceedings{Dean_2013_ICCV_Workshops,author = {Dean, Thomas and Ruzon, Mark A. and Segal, Mark and Shlens, Jonathon and Vijayanarasimhan, Sudheendra and Yagnik, Jay},title = {Fast, Accurate Detection of 100,000 Object Classes on a Single Machine},booktitle = {Proceedings of the IEEE Conference on Computer Vision and... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Dean_Fast_Accurate_Detection_2013_CVPR_paper.pdf |
Shape from Silhouette Probability Maps: Reconstruction of Thin Objects in the Presence of Silhouette Extraction and Calibration Error | Amy Tabb | This paper considers the problem of reconstructing the shape of thin, texture-less objects such as leafless trees when there is noise or deterministic error in the silhouette extraction step or there are small errors in camera calibration. Traditional intersection-based techniques such as the visual hull are not robust... | 2013/Tabb_Shape_from_Silhouette_2013_CVPR_paper.pdf | @InProceedings{Tabb_2013_ICCV_Workshops,author = {Tabb, Amy},title = {Shape from Silhouette Probability Maps: Reconstruction of Thin Objects in the Presence of Silhouette Extraction and Calibration Error},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},y... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Tabb_Shape_from_Silhouette_2013_CVPR_paper.pdf |
Supervised Kernel Descriptors for Visual Recognition | Peng Wang, Jingdong Wang, Gang Zeng, Weiwei Xu, Hongbin Zha, Shipeng Li | In visual recognition tasks, the design of low level image feature representation is fundamental. The advent of local patch features from pixel attributes such as SIFT and LBP, has precipitated dramatic progresses. Recently, a kernel view of these features, called kernel descriptors (KDES) [1], generalizes the feature ... | 2013/Wang_Supervised_Kernel_Descriptors_2013_CVPR_paper.pdf | @InProceedings{Wang_2013_ICCV_Workshops,author = {Wang, Peng and Wang, Jingdong and Zeng, Gang and Xu, Weiwei and Zha, Hongbin and Li, Shipeng},title = {Supervised Kernel Descriptors for Visual Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June}... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wang_Supervised_Kernel_Descriptors_2013_CVPR_paper.pdf |
Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation | Jordi Pont-Tuset, Ferran Marques | This paper tackles the supervised evaluation of image segmentation algorithms. First, it surveys and structures the measures used to compare the segmentation results with a ground truth database; and proposes a new measure: the precision-recall for objects and parts. To compare the goodness of these measures, it define... | 2013/Pont-Tuset_Measures_and_Meta-Measures_2013_CVPR_paper.pdf | @InProceedings{Pont-Tuset_2013_ICCV_Workshops,author = {Pont-Tuset, Jordi and Marques, Ferran},title = {Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Pont-Tuset_Measures_and_Meta-Measures_2013_CVPR_paper.pdf |
A Fast Approximate AIB Algorithm for Distributional Word Clustering | Lei Wang, Jianjia Zhang, Luping Zhou, Wanqing Li | Distributional word clustering merges the words having similar probability distributions to attain reliable parameter estimation, compact classification models and even better classification performance. Agglomerative Information Bottleneck (AIB) is one of the typical word clustering algorithms and has been applied to ... | 2013/Wang_A_Fast_Approximate_2013_CVPR_paper.pdf | @InProceedings{Wang_2013_ICCV_Workshops,author = {Wang, Lei and Zhang, Jianjia and Zhou, Luping and Li, Wanqing},title = {A Fast Approximate AIB Algorithm for Distributional Word Clustering},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wang_A_Fast_Approximate_2013_CVPR_paper.pdf |
Separable Dictionary Learning | Simon Hawe, Matthias Seibert, Martin Kleinsteuber | Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries are either available analytically, or can be learned from a suitable training set. While analytic dictionaries permit to capture the global st... | 2013/Hawe_Separable_Dictionary_Learning_2013_CVPR_paper.pdf | @InProceedings{Hawe_2013_ICCV_Workshops,author = {Hawe, Simon and Seibert, Matthias and Kleinsteuber, Martin},title = {Separable Dictionary Learning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Hawe_Separable_Dictionary_Learning_2013_CVPR_paper.pdf |
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. In comparison to other types of behavior, adversarial behavior is heavily structured as the location of a player (or agent) is dependent both on their teammates and adversaries, in addition to the tactics or... | 2013/Lucey_Representing_and_Discovering_2013_CVPR_paper.pdf | @InProceedings{Lucey_2013_ICCV_Workshops,author = {Lucey, Patrick and Bialkowski, Alina and Carr, Peter and Morgan, Stuart and Matthews, Iain and Sheikh, Yaser},title = {Representing and Discovering Adversarial Team Behaviors Using Player Roles},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pat... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lucey_Representing_and_Discovering_2013_CVPR_paper.pdf |
Object-Centric Anomaly Detection by Attribute-Based Reasoning | Babak Saleh, Ali Farhadi, Ahmed Elgammal | When describing images, humans tend not to talk about the obvious, but rather mention what they find interesting. We argue that abnormalities and deviations from typicalities are among the most important components that form what is worth mentioning. In this paper we introduce the abnormality detection as a recognition... | 2013/Saleh_Object-Centric_Anomaly_Detection_2013_CVPR_paper.pdf | @InProceedings{Saleh_2013_ICCV_Workshops,author = {Saleh, Babak and Farhadi, Ali and Elgammal, Ahmed},title = {Object-Centric Anomaly Detection by Attribute-Based Reasoning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Saleh_Object-Centric_Anomaly_Detection_2013_CVPR_paper.pdf |
Cartesian K-Means | Mohammad Norouzi, David J. Fleet | A fundamental limitation of quantization techniques like the k-means clustering algorithm is the storage and runtime cost associated with the large numbers of clusters required to keep quantization errors small and model fidelity high. We develop new models with a compositional parameterization of cluster centers, so r... | 2013/Norouzi_Cartesian_K-Means_2013_CVPR_paper.pdf | @InProceedings{Norouzi_2013_ICCV_Workshops,author = {Norouzi, Mohammad and Fleet, David J.},title = {Cartesian K-Means},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Norouzi_Cartesian_K-Means_2013_CVPR_paper.pdf |
Optimal Geometric Fitting under the Truncated L2-Norm | Erik Ask, Olof Enqvist, Fredrik Kahl | This paper is concerned with model fitting in the presence of noise and outliers. Previously it has been shown that the number of outliers can be minimized with polynomial complexity in the number of measurements. This paper improves on these results in two ways. First, it is shown that for a large class of problems, t... | 2013/Ask_Optimal_Geometric_Fitting_2013_CVPR_paper.pdf | @InProceedings{Ask_2013_ICCV_Workshops,author = {Ask, Erik and Enqvist, Olof and Kahl, Fredrik},title = {Optimal Geometric Fitting under the Truncated L2-Norm},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ask_Optimal_Geometric_Fitting_2013_CVPR_paper.pdf |
Pedestrian Detection with Unsupervised Multi-stage Feature Learning | Pierre Sermanet, Koray Kavukcuoglu, Soumith Chintala, Yann Lecun | Pedestrian detection is a problem of considerable practical interest. 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. The model uses a few new twists, such as multi-st... | 2013/Sermanet_Pedestrian_Detection_with_2013_CVPR_paper.pdf | @InProceedings{Sermanet_2013_ICCV_Workshops,author = {Sermanet, Pierre and Kavukcuoglu, Koray and Chintala, Soumith and Lecun, Yann},title = {Pedestrian Detection with Unsupervised Multi-stage Feature Learning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {J... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Sermanet_Pedestrian_Detection_with_2013_CVPR_paper.pdf |
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. Our model has three distinguishing features: (i) large appearance differences between people are handled compositionally by allowing parts or collections of parts to be substituted with alternative variants, (ii) each variant... | 2013/Rothrock_Integrating_Grammar_and_2013_CVPR_paper.pdf | @InProceedings{Rothrock_2013_ICCV_Workshops,author = {Rothrock, Brandon and Park, Seyoung and Zhu, Song-Chun},title = {Integrating Grammar and Segmentation for Human Pose Estimation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Rothrock_Integrating_Grammar_and_2013_CVPR_paper.pdf |
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. The system builds on established tracking and mapping techniques to exploit incremental 3D reconstruction in order to validate hypotheses on th... | 2013/Fioraio_Joint_Detection_Tracking_2013_CVPR_paper.pdf | @InProceedings{Fioraio_2013_ICCV_Workshops,author = {Fioraio, Nicola and Di Stefano, Luigi},title = {Joint Detection, Tracking and Mapping by Semantic Bundle Adjustment},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Fioraio_Joint_Detection_Tracking_2013_CVPR_paper.pdf |
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. Our approach employs a regression forest that is capable of inferring an estimate of each pixel's correspondence to 3D points in the scene's world coordinate frame. The forest uses only simp... | 2013/Shotton_Scene_Coordinate_Regression_2013_CVPR_paper.pdf | @InProceedings{Shotton_2013_ICCV_Workshops,author = {Shotton, Jamie and Glocker, Ben and Zach, Christopher and Izadi, Shahram and Criminisi, Antonio and Fitzgibbon, Andrew},title = {Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images},booktitle = {Proceedings of the IEEE Conference on Computer... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Shotton_Scene_Coordinate_Regression_2013_CVPR_paper.pdf |
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. Our method begins with partitioning the input images into a set of superpixels, followed by seeking the optimal superpixel-pair affinity matrix, both of which are performed at multiple scales of the input images. Since low... | 2013/Liu_Robust_Region_Grouping_2013_CVPR_paper.pdf | @InProceedings{Liu_2013_ICCV_Workshops,author = {Liu, Xiaobai and Lin, Liang and Yuille, Alan L.},title = {Robust Region Grouping via Internal Patch Statistics},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Liu_Robust_Region_Grouping_2013_CVPR_paper.pdf |
Boundary Detection Benchmarking: Beyond F-Measures | Xiaodi Hou, Alan Yuille, Christof Koch | For an ill-posed problem like boundary detection, human labeled datasets play a critical role. Compared with the active research on finding a better boundary detector to refresh the performance record, there is surprisingly little discussion on the boundary detection benchmark itself. The goal of this paper is to ident... | 2013/Hou_Boundary_Detection_Benchmarking_2013_CVPR_paper.pdf | @InProceedings{Hou_2013_ICCV_Workshops,author = {Hou, Xiaodi and Yuille, Alan and Koch, Christof},title = {Boundary Detection Benchmarking: Beyond F-Measures},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Hou_Boundary_Detection_Benchmarking_2013_CVPR_paper.pdf |
Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes | Srikumar Ramalingam, Jaishanker K. Pillai, Arpit Jain, Yuichi Taguchi | Junctions are strong cues for understanding the geometry of a scene. In this paper, we consider the problem of detecting junctions and using them for recovering the spatial layout of an indoor scene. Junction detection has always been challenging due to missing and spurious lines. We work in a constrained Manhattan wor... | 2013/Ramalingam_Manhattan_Junction_Catalogue_2013_CVPR_paper.pdf | @InProceedings{Ramalingam_2013_ICCV_Workshops,author = {Ramalingam, Srikumar and Pillai, Jaishanker K. and Jain, Arpit and Taguchi, Yuichi},title = {Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mon... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Ramalingam_Manhattan_Junction_Catalogue_2013_CVPR_paper.pdf |
Detection- and Trajectory-Level Exclusion in Multiple Object Tracking | Anton Milan, Konrad Schindler, Stefan Roth | When tracking multiple targets in crowded scenarios, modeling mutual exclusion between distinct targets becomes important at two levels: (1) in data association, each target observation should support at most one trajectory and each trajectory should be assigned at most one observation per frame; (2) in trajectory esti... | 2013/Milan_Detection-_and_Trajectory-Level_2013_CVPR_paper.pdf | @InProceedings{Milan_2013_ICCV_Workshops,author = {Milan, Anton and Schindler, Konrad and Roth, Stefan},title = {Detection- and Trajectory-Level Exclusion in Multiple Object Tracking},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Milan_Detection-_and_Trajectory-Level_2013_CVPR_paper.pdf |
What Makes a Patch Distinct? | Ran Margolin, Ayellet Tal, Lihi Zelnik-Manor | What makes an object salient? Most previous work assert that distinctness is the dominating factor. The difference between the various algorithms is in the way they compute distinctness. Some focus on the patterns, others on the colors, and several add high-level cues and priors. We propose a simple, yet powerful, algo... | 2013/Margolin_What_Makes_a_2013_CVPR_paper.pdf | @InProceedings{Margolin_2013_ICCV_Workshops,author = {Margolin, Ran and Tal, Ayellet and Zelnik-Manor, Lihi},title = {What Makes a Patch Distinct?},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Margolin_What_Makes_a_2013_CVPR_paper.pdf |
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. By combining dense motion and stereo cues with sparse keypoint correspondences, and by feeding back information from the model to the cue extraction level, the meth... | 2013/Pauwels_Real-Time_Model-Based_Rigid_2013_CVPR_paper.pdf | @InProceedings{Pauwels_2013_ICCV_Workshops,author = {Pauwels, Karl and Rubio, Leonardo and Diaz, Javier and Ros, Eduardo},title = {Real-Time Model-Based Rigid Object Pose Estimation and Tracking Combining Dense and Sparse Visual Cues},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recogn... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Pauwels_Real-Time_Model-Based_Rigid_2013_CVPR_paper.pdf |
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. We propose a generalized and mathematically sound L 0 spar... | 2013/Xu_Unnatural_L0_Sparse_2013_CVPR_paper.pdf | @InProceedings{Xu_2013_ICCV_Workshops,author = {Xu, Li and Zheng, Shicheng and Jia, Jiaya},title = {Unnatural L0 Sparse Representation for Natural Image Deblurring},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Xu_Unnatural_L0_Sparse_2013_CVPR_paper.pdf |
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 introduce a new problem domain for activity recognition: the analysis of children's social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental dis... | 2013/Rehg_Decoding_Childrens_Social_2013_CVPR_paper.pdf | @InProceedings{Rehg_2013_ICCV_Workshops,author = {Rehg, J. and Abowd, G. and Rozga, A. and Romero, M. and Clements, M. and Sclaroff, S. and Essa, I. and Ousley, O. and Li, Y. and Kim, C. and Rao, H. and Kim, J. and Lo Presti, L. and Zhang, J. and Lantsman, D. and Bidwell, J. and Ye, Z.},title = {Decoding Children's Soc... | https://openaccess.thecvf.com/content_cvpr_2013/papers/Rehg_Decoding_Childrens_Social_2013_CVPR_paper.pdf |
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. In contrast to existing methods, the proposed Least Soft-thresold Squares (LSS) algorithm models the error term with the Gaussian-Laplacian distribution, which can be solved efficiently. Based on maximum joint li... | 2013/Wang_Least_Soft-Threshold_Squares_2013_CVPR_paper.pdf | @InProceedings{Wang_2013_ICCV_Workshops,author = {Wang, Dong and Lu, Huchuan and Yang, Ming-Hsuan},title = {Least Soft-Threshold Squares Tracking},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Wang_Least_Soft-Threshold_Squares_2013_CVPR_paper.pdf |
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. Given a pre-defined gallery of short exemplar interaction videos, and a long input video of a large gathering (with approximately-tracked agents), we identify within the gathering small su... | 2013/Li_Finding_Group_Interactions_2013_CVPR_paper.pdf | @InProceedings{Li_2013_ICCV_Workshops,author = {Li, Ruonan and Porfilio, Parker and Zickler, Todd},title = {Finding Group Interactions in Social Clutter},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Li_Finding_Group_Interactions_2013_CVPR_paper.pdf |
Online Robust Dictionary Learning | Cewu Lu, Jiaping Shi, Jiaya Jia | Online dictionary learning is particularly useful for processing large-scale and dynamic data in computer vision. It, however, faces the major difficulty to incorporate robust functions, rather than the square data fitting term, to handle outliers in training data. In this paper, we propose a new online framework enabl... | 2013/Lu_Online_Robust_Dictionary_2013_CVPR_paper.pdf | @InProceedings{Lu_2013_ICCV_Workshops,author = {Lu, Cewu and Shi, Jiaping and Jia, Jiaya},title = {Online Robust Dictionary Learning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Lu_Online_Robust_Dictionary_2013_CVPR_paper.pdf |
Learning the Change for Automatic Image Cropping | Jianzhou Yan, Stephen Lin, Sing Bing Kang, Xiaoou Tang | Image cropping is a common operation used to improve the visual quality of photographs. 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. Our approach utilizes a lar... | 2013/Yan_Learning_the_Change_2013_CVPR_paper.pdf | @InProceedings{Yan_2013_ICCV_Workshops,author = {Yan, Jianzhou and Lin, Stephen and Bing Kang, Sing and Tang, Xiaoou},title = {Learning the Change for Automatic Image Cropping},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2013}} | https://openaccess.thecvf.com/content_cvpr_2013/papers/Yan_Learning_the_Change_2013_CVPR_paper.pdf |
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