Camera Ready Copies
CVPR Main Conference Camera Ready Copy Instructions
UPLOAD on CMT BY 11:59 PM PDT APRIL 4, 2011
There are 4 steps. formatting your paper (with page numbers), submitting the copyright form to IEEE, verifying that your paper is compliant with IEEE's requirements for PDF files, and finally submitting the camera-ready paper. Also don't forget that one author from each paper should register for the conference and make arrangements to be there to present. Non-presented papers may not appear in Xplore. Please follow the instructions CAREFULLY; failure to complete any of these requirements may result in your paper being removed from CVPR 2011 publication.
Step 1: Formating and Page Numbering
This year there has been a change in CVPR publishing. You, the authors, are required to add the final page numbers to your papers. (In the past we have paid a company thousands to add them.) The table below has the starting page for your paper and your pages should be numbered consecutively. For page numbering we allocated everyone 8 pages, but that does not mean the added pages are free. Note that you get 6 pages free and $100 extra for each added page(maximum=8).
Windows/Word template was updated or users can simply add a footer with page numbers, centered and .85 inches from the bottom of the page and make it start at the correct page number rather than the 4321 in the example (how to do that depends on your version of Word).
For unix/latex users, we have updated the latex final paper template, but it may also be easier for people to patch their existing files by setting the page counter and commenting out the line that made all pages empty (orginally line 23) (add a % as in the following)
%\ifcvprfinal\pagestyle{empty}\fi \setcounter{page}{4321}
and then commenting out the firstpage being empty on line 46
%\thispagestyle{empty}
Failure to use the correct page number, or failure to place it properly, could result in the paper not being included in Xplore, even if it passes PDF express, which does not check page numbers!
Step 2: Instructions for electronic submission of IEEE copyright form (eCF)
NEW IMPORTANT CHANGE: If you need to make changes to the title or author list, you should be able to directly edit in CMT. The title/authors in the copyright form must match exactly.
eCF is done through CMT. Please log in to https://cmt.research.microsoft.com/CVPR2011 and do the following:
- For those who are area chairs or reviewers for CVPR 2011, go to the Author console. For all others, the Author console is the default page.
- Click on the Submit IEEE Copyright form link at the rightmost column (which initiates eCF). Please read instructions CAREFULLY.
- You need to go through eCF for EACH paper separately.
- Since eCF can only be done ONCE for each paper, it is important that only one person (contact author) work on it per paper.
- Once eCF has been completed, IEEE will email all the authors as verification.
Step 3: Instructions for verifying compliance of the final version of your paper
- Make sure your PDF file is IEEE compliant. If your file is noncompliant, it WILL NOT be included by IEEE in Xplore, which means your paper will not be considered as published.
- The easiest way to check for PDF compliance is to use the PDF eXpress web site (http://www.pdf-express.org). Click on the link "New Users - Click Here" and fill in your information. You will need the Conference ID which is: cvpr11x
- Follow the links at www.ieee.org/confpubcenter for information on the specific elements of PDF compliance. The most frequent cause of noncompliant files is the use of a custom font that is not embedded in the PDF file. You must ensure that all fonts in the document (including those in figure captions, tables, and figure bodies/legends) are embedded.
- This is a basic check for PDF correctness, and does not insure you followed all rules. IEEE may still reject papers that have not followed the instructions, e.g. violations of font, margins or lack of correct page numbers. You will not have a chance to correct anything after submission, so double check you are following the rules.
NOTE: The PDF eXpress validation process is NOT the final paper submission process. Once your paper is valid, you must follow instruction step 4 below.
Step 4. Instructions for submitting camera-ready paper using CMT
The camera-ready paper is submitted through CMT. Please log in to https://cmt.research.microsoft.com/CVPR2011 and do the following:
- For those who are area chairs or reviewers for CVPR 2011, go to the Author console. For all others, the Author console is the default page.
- CMT will not rename/number your files, so please use the following naming/paging convention:
- For the camera-ready file, name must be of the form XXXX.pdf, where XXXX is your four-digit number paper ID (zero-pad if necessary). E.g., if your paper ID is 23, the filename should be 0023.pdf.
- Page numbering: your camera-ready paper should include page numbers starting as described above. This is different than in past years.
- If you wish to load a supplementary file, load the camera-ready file FIRST, then the supplementary file (loading is sequential).
- For the supplementary file, name must be of the form XXXX-supp.YYY, where XXXX is the same as above, and YYY is either pdf or zip only.
Please limit the combined size to 20 MB. Note Supplemental material will NOT be in Xplore and depending on space constraints may also not be in the actual conference memory-sticks. We strongly recommend you consider placing the supplemental material on the web and including a link in your paper (so that readers in Xplore can eventually find it).
Table of Page numbers for CVPR main conference papers.
ID | Paper Starts on Page | Title | All Authors | Status | Primary Subject Area |
1531 | 1 | 3D Motion Reconstruction for Real-World Camera Motion | Yingying Zhu (University of Queensland); Mark Cox;Simon Lucey; | Poster | Applications of Computer Vision |
96 | 9 | A fully automated greedy square jigsaw puzzle solver | Dolev Pomeranz (Ben Gurion University); Michal Shemesh (Ben Gurion University); Ohad Ben-Shahar (Ben-Gurion University); | Poster | Applications of Computer Vision |
1235 | 17 | A Multichannel Edge-Weighted Centroidal Voronoi Tessellation Algorithm for 3D Superalloy Image Segmentation | Yu Cao (University of South Carolina); Lili Ju (University of South Carolina); Qin Zou (University of South Carolina); Chengzhang Qu (Wuhan University, China); Song Wang; | Poster | Applications of Computer Vision |
1523 | 25 | A Unified Framework for Locating and Recognizing Human Actions | Yuelei Xie (Institute of computing technology, Chinese Academy of Science); Hong Chang;Zhe Li (Institute of computing technology, Chinese Academy of Science); Luhong Liang (Institute of computing technology, Chinese Academy of Science); Xilin Chen;Debin Zhao; | Poster | Applications of Computer Vision |
971 | 33 | Aesthetic Quality Classification of Photographs Based on Color Harmony | Masashi Nishiyama (University of Tokyo); Takahiro Okabe;Imari Sato;Yoichi Sato; | Poster | Applications of Computer Vision |
1874 | 41 | Automatic Photo-to-Terrain Alignment for the Annotation of Mountain Pictures | Lionel Baboud (MPI Informatik); Martin Cadik (MPI Informatik); Elmar Eisemann (MPI Informatik, Telecom ParisTech); Hans-Peter Seidel (MPI Informatik); | Oral | Applications of Computer Vision |
506 | 49 | Constructing Image Panoramas using Dual-Homography Warping | Junhong GAO (NUS); Michael Brown;Seon Joo Kim; | Poster | Applications of Computer Vision |
1561 | 57 | Distributed Computer Vision Algorithms Through Distributed Averaging | Roberto Tron (Johns Hopkins University); René Vidal; | Poster | Applications of Computer Vision |
1950 | 65 | Efficient Multi-Camera Detection, Tracking, and Identification using a Shared Set of Haar-Features | Reyes Rios-Cabrera (K.U.Leuven); Tinne Tuytelaars (K.U.Leuven); Luc VanGool; | Poster | Applications of Computer Vision |
1765 | 73 | Enforcing Similarity Constraints with Integer Programming for Better Scene Text Recognition | David Smith (UMass Amherst); Jacqueline Feild (UMass Amherst); Eric Learned-Miller; | Poster | Applications of Computer Vision |
637 | 81 | High Precision localization System with Visual Landmarks Fused With Range Data | Zhiwei Zhu (Sarnoff Corporation); | Poster | Applications of Computer Vision |
571 | 89 | Importance Filtering for Image Retargeting | Yuanyuan Ding (Epson Research and Development); Jing Xiao (Epson R&D); | Poster | Applications of Computer Vision |
430 | 97 | Learning photographic global tonal adjustments with a database of input/output image pairs | Vladimir Bychkovsky (MIT / CSAIL); Sylvain Paris;Eric Chan (Adobe Systems Inc.); Fredo Durand (MIT); | Poster | Applications of Computer Vision |
331 | 105 | Predicting Image Matching using Affine Distortion Models | Daniel Fleck (American University); Zoran Duric; | Poster | Applications of Computer Vision |
976 | 113 | RUNE-Tag: a High Accuracy Fiducial Marker with Strong Occlusion Resilience | Filippo Bergamasco (Università Ca' Foscari Venezia); Andrea Albarelli;Andrea Torsello;Emanuele Rodola (Università Ca' Foscari Venezia); | Poster | Applications of Computer Vision |
791 | 121 | Sparse Approximated Nearest Points for Image Set Classification | Yiqun Hu (University of Western Australia); Ajmal Mian (University of Western Australia); Robyn Owens (University of Western Australia); | Oral | Applications of Computer Vision |
1183 | 129 | The Magic Sigma | Dirk Padfield (GE Global Research); | Poster | Applications of Computer Vision |
162 | 137 | Towards a practical lipreading system | Ziheng Zhou (University of Oulu); Matti Pietik;Guoying Zhao (University of Oulu, Finland); | Poster | Applications of Computer Vision |
1842 | 145 | What makes an image memorable? | Phillip Isola (MIT); Jianxiong Xiao (MIT CSAIL); Aude Oliva;Antonio Torralba; | Poster | Applications of Computer Vision |
464 | 153 | An $L_1$-based variational model for Retinex theory and its application to medical images | Wenye Ma (UCLA); Jean-Michel Morel (CMLA); Stanley Osher (UCLA); Aichi Chien (UCLA); | Poster | Color and Texture |
123 | 161 | Inertial sensor-aligned visual feature descriptors | Daniel Kurz (Metaio); Selim Ben Himane (metaio GmbH); | Poster | Color and Texture |
1782 | 169 | Learning Object Color Models from Multi-view Constraints | Trevor Owens (UC Berkeley); Kate Saenko;Trevor Darrell (ICSI, UC Berkeley); Ayan Chakrabarti;Todd Zickler; | Poster | Color and Texture |
1484 | 177 | Multi-spectral SIFT for Scene Category Recognition | Matthew Brown;Sabine Susstrunk (EPFL); | Poster | Color and Texture |
1781 | 185 | Separating Reflective and Fluorescent Components of An Image | Cherry Zhang (University of Waterloo); Imari Sato; | Oral | Color and Texture |
1585 | 193 | Statistics of Real-World Hyperspectral Images | Ayan Chakrabarti;Todd Zickler; | Poster | Color and Texture |
1575 | 201 | Unsupervised Local Color Correction for Coarsely Registered Images | Miguel Riem de Oliveira (University of Aveiro); Angel Sappa (Computer Vision Center); Vitor Santos (University of Aveiro, Portugal); | Poster | Color and Texture |
1341 | 209 | A Bayesian Approach to Adaptive Video Super Resolution | Ce Liu (Microsoft Research New England); Deqing Sun; | Oral | Computational Photography and Video |
1350 | 217 | A Theory of Multi-perspective Defocusing | Yuanyuan Ding (Epson Research and Development); Jingyi Yu; | Poster | Computational Photography and Video |
889 | 225 | Auto Directed Video Stabilization with Robust L1 Optimal Camera Paths | Matthias Grundmann;Vivek Kwatra;Irfan Essa; | Poster | Computational Photography and Video |
874 | 233 | Blind Deconvolution Using A Normalized Sparsity Measure | Dilip Krishnan (New York University); Rob Fergus; | Poster | Computational Photography and Video |
698 | 241 | Blur kernel estimation using the Radon Transform | Taeg Sang Cho (MIT CSAIL); Sylvain Paris;Bill Freeman;Berthold Horn (MIT CSAIL); | Poster | Computational Photography and Video |
538 | 249 | Collaborative Personalization of Image Enhancement | Juan Caicedo (Universidad Nacional de Colomb); Ashish Kapoor;Sing Bing Kang (Microsoft Research); | Poster | Computational Photography and Video |
431 | 257 | Enhancing by Saliency-guided Decolorization | Codruta Ancuti (Hasselt University); Cosmin Ancuti (Hasselt University); Philippe Bekaert (Hasselt University); | Poster | Computational Photography and Video |
652 | 265 | Estimating Motion and Size of Moving Non-Line-of-Sight Objects in Cluttered Environments | Rohit Pandharkar (MIT); Andreas Velten (MIT); Andrew Bardagjy (MIT); Ramesh Raskar;Moungi Bawendi;Ahmed Kirmani;Everett Lawson (MIT); | Poster | Computational Photography and Video |
180 | 273 | Exploring Aligned Complementary Image Pair for Blind Motion Deblurring | Wen Li (School of Electronics and Info); Jun Zhang (School of Electronics and Information Engineering, Beihang University); Qionghai Dai (Tsinghua University); | Poster | Computational Photography and Video |
680 | 281 | Face Illumination Transfer through Edge-preserving Filters | Xiaowu Chen (Beihang University); Mengmeng Chen (Beihang University); Xin Jin (Beihang University); Qinping Zhao (Beihang University); | Poster | Computational Photography and Video |
108 | 289 | Glare Encoding of High Dynamic Range Images | Mushfiqur Rouf (University of British Columbia); Rafal Mantiuk (Bangor University); Wolfgang Heidrich;Matthew Trentacoste (University of British Columbia); Cheryl Lau (University of British Columbia); | Oral | Computational Photography and Video |
445 | 297 | High Resolution Multispectral Video Capture with a Hybrid Camera System | Xun Cao (Tsinghua University); Xin Tong;Qionghai Dai (Tsinghua University); Stephen Lin; | Poster | Computational Photography and Video |
576 | 305 | Learning a Blind Measure of Perceptual Image Quality | Huixuan Tang (University of Toronto); Neel Joshi;Ashish Kapoor; | Poster | Computational Photography and Video |
279 | 313 | Motion Denoising with Application to Time-lapse Photography | Michael Rubinstein (MIT CSAIL); Ce Liu (Microsoft Research New England); Bill Freeman; | Poster | Computational Photography and Video |
267 | 321 | Noise Suppression in Low-Light Images through Joint Denoising and Demosaicing | Priyam Chatterjee (UC Santa Cruz); Neel Joshi;Sing Bing Kang (Microsoft Research); Yasuyuki Matsushita; | Poster | Computational Photography and Video |
974 | 329 | P2C2: Programmable Pixel Compressive Camera for High Speed Imaging. | Dikpal Reddy (University of Maryland); Ashok Veeraraghavan; | Poster | Computational Photography and Video |
1348 | 337 | Reconstructing an image from its local descriptors | Philippe Weinzaepfel (ENS Cachan Bretagne); Herve Jegou;Patrick Perez (Technicolor); | Poster | Computational Photography and Video |
26 | 345 | Smoothly Varying Affine Stitching | Wen Yan Lin (I2R); Siying Liu (i2r.a-star.edu.sg); Yasuyuki Matsushita;Tian Tsong Ng (i2r.a-star.edu.sg); Loong Fah Cheong (NUS); | Oral | Computational Photography and Video |
1193 | 353 | Three-Dimensional Kaleidoscopic Imaging | Ilya Reshetouski (Saarland University); Alkhazur Manakov (Saarland University); Hans-Peter Seidel (MPI Informatik); Ivo Ihrke; | Oral | Computational Photography and Video |
118 | 361 | Wide-angle Micro Sensors for Vision on a Tight Budget | Sanjeev Koppal;Todd Zickler;Ioannis Gkioulekas (Harvard University); | Oral | Computational Photography and Video |
1107 | 369 | An effective document image deblurring algorithm | Xiao-gang Chen (Shanghai Jiao Tong University ); Xiangjian He (University of Technology, Syd); Jie Yang (Shanghai Jiaotong University); Qiang Wu (UTS); | Poster | Document Analysis |
972 | 377 | Rectification and 3D reconstruction of Curved Document Images | Yuandong Tian (Carnegie Mellon University); Srinivasa Narasimhan; | Oral | Document Analysis |
1398 | 385 | Registration of Camera Captured Documents Under Non-rigid Deformation | Venkata Edupuganti (Dept. of CS, NJIT); Suryaprakash Kompalli (Hewlett Packard Labs); Vinayak Agarwal (Hewlet Packard Labs, India); | Poster | Document Analysis |
1588 | 393 | Style Transfer Matrix Learning for Unsupervised Writer Adaptation | Xu-Yao Zhang (National Laboratory of Pattern Recognition, Chinese Academy of Sciences); Cheng-Lin Liu (CASIA); | Poster | Document Analysis |
1888 | 401 | A Probabilistic Model for Recursive Factorized Image Features | Sergey Karayev (UC Berkeley); Mario Fritz;Sanja Fidler (University of Ljubljana); Trevor Darrell (ICSI, UC Berkeley); | Poster | Early and Biologically-inspired Vision |
159 | 409 | Global Contrast based Salient Region Detection | Ming-Ming Cheng (Tsinghua University); Guo-Xin Zhang (Tsinghua University); Niloy Mitra (IIT Delhi / KAUST); Xiaolei Huang;Shi-Min Hu (Tsinghua University); | Poster | Early and Biologically-inspired Vision |
1987 | 417 | Image Saliency: From Local to Global Context | Meng Wang (Boston University); Janusz Konrad (Boston University); Prakash Ishwar (Boston University); Yushi Jing (Google Research); Henry Rowley (Google); | Poster | Early and Biologically-inspired Vision |
1770 | 425 | On analyzing video with very small motions | Robert Pless;Nathan Jacobs (University of Kentucky); Michael Dixon (Washington University in St. Louis); Austin Abrams (Washington University in St. Louis); | Poster | Early and Biologically-inspired Vision |
813 | 433 | Saliency Estimation Using a Non-Parametric Low-Level Vision Model | Naila Murray (Computer Vision Centre); Maria Vanrell;Xavier Otazu;C. Alejandro Parraga; | Poster | Early and Biologically-inspired Vision |
470 | 441 | Simulating Human Saccadic Scanpaths on Natural Images | Wei Wang (Graduate University of Chinese Academy and Sciences); Cheng Chen;Yizhou Wang;Tingting Jiang (School of EECS, Peking University); Fang Fang;Yuan Yao; | Poster | Early and Biologically-inspired Vision |
1805 | 449 | Single Image Super-Resolution using Gaussian Process Regression | He He (The Hong Kong Polytechnic Univ); Wan-Chi Siu (The Hong Kong Polytechnic University); | Poster | Early and Biologically-inspired Vision |
697 | 457 | Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering | Weisheng Dong;Xin Li (WVU); | Oral | Early and Biologically-inspired Vision |
1645 | 465 | The importance of intermediate representations for the modeling of 2D shape detection: Endstopping and curvature tuned computations | Antonio Rodriguez-Sanchez (York University); John Tsotsos; | Poster | Early and Biologically-inspired Vision |
1673 | 473 | Visual Saliency Detection by Spatially Weighted Dissimilarity | Lijuan duan;chunpeng Wu;Jun Miao (ICT, CAS); Laiyun Qing;Yu Fu; | Poster | Early and Biologically-inspired Vision |
1689 | 481 | A RankOrder-based clustering algorithm in face annotation | Chunhui Zhu (Tsinghua University); Fang Wen (Microsoft Research Asia); Jian Sun; | Poster | Face and Gesture Analysis |
1397 | 489 | Action Recognition using Context and Appearance Distribution Features | Xinxiao Wu (NTU); Dong Xu;Lixin Duan (NTU, Singapore); Jiebo Luo; | Poster | Face and Gesture Analysis |
765 | 497 | An Associate-Predict Model for Face Recognition | Qi Yin;Jian Sun;Xiaoou Tang; | Poster | Face and Gesture Analysis |
712 | 505 | Correspondence Driven Adaptation for Human Profile Recognition | Ming Yang (NEC Laboratories America); Shenghuo Zhu (NEC Laboratories America); Fengjun Lv (NEC Laboratories America); Kai Yu; | Poster | Face and Gesture Analysis |
63 | 513 | Coupled Information-Theoretic Encoding for Face Photo-Sketch Recognition | Wei Zhang (CUHK); Xiaogang Wang (The Chinese University of Hong Kong); Xiaoou Tang; | Oral | Face and Gesture Analysis |
1826 | 521 | Exploiting Phonological Constraints for Handshape Inference in ASL Video | Ashwin Thangali (Boston Univsersity); Stan Sclaroff (Boston University); Carol Neidle (Boston University); Joan Nash (Boston University); | Poster | Face and Gesture Analysis |
1105 | 529 | Face Recognition in Unconstrained Videos with Matched Background Similarity | Lior Wolf;Tal Hassner;Itay Maoz (Tel-Aviv University); | Poster | Face and Gesture Analysis |
1033 | 537 | Face Recognition with Large Pose Variation | Carlos Castillo;David Jacobs; | Poster | Face and Gesture Analysis |
1291 | 545 | Finding Fiducial Points with Local Detectors and a Consensus of Global Models | Peter Belhumeur;David Jacobs (UMIACS); David Kriegman (UCSD/KBVT); | Poster | Face and Gesture Analysis |
1020 | 553 | Is face recognition really a Compressive Sensing problem? | Qinfeng Shi (The University of Adelaide); Anders Eriksson (University of Adelaide); Anton vandenHengel;Chunhua Shen (NICTA); | Poster | Face and Gesture Analysis |
301 | 561 | Joint Face Alignment with A Generic Deformable Face Model | Cong Zhao (Chinese University of Hong Kon); Wai-Kuen Cham;Xiaogang Wang (The Chinese University of Hong Kong); | Poster | Face and Gesture Analysis |
363 | 569 | Non-negative Local Coordinate Factorization for Image Representation | Yan Chen (Zhejiang University); Xiaofei He; | Poster | Face and Gesture Analysis |
48 | 577 | Online Domain-Adaptation of a Pre-Trained Cascade of Classifiers | Vidit Jain (Yahoo! Labs); Eric Learned-Miller; | Oral | Face and Gesture Analysis |
523 | 585 | Ordinal Hyperplanes Ranker with Cost Sensitivities for Age Estimation | Kuang-Yu Chang (Academia Sinica); Chu-Song Chen (Academia Sinica); Yi-Ping Hung (NTU); | Poster | Face and Gesture Analysis |
176 | 593 | PLS Based Multi-Modal Face Recognition | Abhishek Sharma (University of Maryland CP); David Jacobs (UMIACS); | Poster | Face and Gesture Analysis |
554 | 601 | Pose-Robust Recognition of Low-Resolution Face Images | Soma Biswas (University of Notre Dame); Gaurav Aggarwal;Patrick Flynn; | Poster | Face and Gesture Analysis |
1669 | 609 | Probabilistic Gaze Estimation Without Active Personal Calibration | Jixu Chen (Rensselaer Polytechnic Inst.); Qiang Ji; | Poster | Face and Gesture Analysis |
619 | 617 | Real Time Head Pose Estimation with Random Regression Forests | Gabriele Fanelli (ETHZ); Juergen Gall;Luc VanGool; | Poster | Face and Gesture Analysis |
341 | 625 | Robust Sparse Coding for Face Recognition | Meng Yang (The Hong Kong Polytechnic University); Lei Zhang (The Hong Kong Polytechnic University); | Poster | Face and Gesture Analysis |
1604 | 633 | Support Tucker Machines | Irene Kotsia (Queen Mary University of Londo); Ioannis Patras; | Poster | Face and Gesture Analysis |
1329 | 641 | Which parts of the face give out your identity? | Jesus Ocegueda-Gonzalez (University of Houston); Shishir Shah (University of Houston); Ioannis Kakadiaris; | Poster | Face and Gesture Analysis |
1278 | 649 | Person Re-identification by Probabilistic Relative Distance Comparison | Wei-Shi Zheng (QUEEN MARY UNIVERSITY OF LONDO); Shaogang Gong;Tao Xiang; | Poster | Human Identification |
388 | 657 | Simultaneous Dimensionality Reduction and Human Age Estimation via Kernel Partial Least Squares Regression | Guodong Guo;Guowang Mu (Hebei University of Technology); | Poster | Human Identification |
930 | 665 | Uncovering Vein Patterns from Color Skin Images for Forensic Analysis | Chaoying Tang (Nanyang Technological Univ.); Adams Wai Kin Kong (Nanyang Technological University ); Noah Craft (Los Angeles Biomedical Research Institute); | Oral | Human Identification |
1228 | 673 | Illumination Estimation and Cast Shadow Detection through a Higher-order Graphical Model | Alexandros Panagopoulos (Stony Brook University); Chaohui Wang (Ecole Centrale Paris/INRIA); Dimitris Samaras;Nikos Paragios; | Poster | Illumination and Reflectance Modeling |
1382 | 681 | Illumination Invariant Feature Extraction Based on Natural Images Statistics and Optimal Filtering | Lu-Hung Chen (UNC at Chapel Hill); Yao-Hsiang Yang (Academia Sinica); Chu-Song Chen (Academia Sinica); Ming-Yen Cheng; | Poster | Illumination and Reflectance Modeling |
157 | 689 | Interreflections removal for photometric stereo by using spectrum-dependent albedo | Miao Liao (University of Kentucky); Xinyu Huang (North Carolina Central University); Ruigang Yang (University of Kentucky); | Poster | Illumination and Reflectance Modeling |
1961 | 697 | Intrinsic Images Decomposition Using a Local and Global Sparse Representation of Reflectance | Li Shen (I2R); Chuohao Yeo (i2r.a-star.edu.sg); | Oral | Illumination and Reflectance Modeling |
1639 | 705 | Reflection Detection in Image Sequences | Mohamed Ahmed (Trinity College Dublin); Francois Pitie;Anil Kokaram; | Poster | Illumination and Reflectance Modeling |
57 | 713 | Structured Light 3D Scanning Under Global Illumination | Mohit Gupta;Amit Agrawal;Ashok Veeraraghavan;Srinivasa Narasimhan; | Poster | Illumination and Reflectance Modeling |
1662 | 721 | Using Specular Highlights as Pose Invariant Features for 2D-3D Pose Estimation | Aaron Netz (University of Haifa); Margarita Osadchy; | Poster | Illumination and Reflectance Modeling |
805 | 729 | Asymmetric Distances for Binary Embeddings | Albert Gordo (CVC / XRCE); Florent Perronnin; | Poster | Image and Video Retrieval |
1319 | 737 | City-Scale Landmark Identification on Mobile Devices | David Chen (Stanford University); Georges Baatz (Department of Computer Science, ETH Zurich); Kevin Koeser;Sam Tsai;Ramakrishna Vedantham (Nokia Research Center, Palo Alto); Timo Pylvanainen (Nokia Research Center, Tampere); kimmo Roimela (Nokia Research Center); Xin Chen (Navteq); Jeff Bach (Navteq); Marc Pollefeys;Bernd Girod;Radek Grzeszczuk; | Poster | Image and Video Retrieval |
1261 | 745 | Combining attributes and Fisher vectors for efficient image retrieval | Matthijs Douze;Arnau Ramisa (INRIA); Cordelia Schmid; | Poster | Image and Video Retrieval |
859 | 753 | Compact Hashing with Joint Optimization of Search Accuracy and Time | Junfeng He (Columbia University); Regunathan Radhakrishnan;Shih-Fu Chang;Claus Bauer; | Oral | Image and Video Retrieval |
630 | 761 | Edgel Inverted Index for Large-Scale Sketch-based Image Search | Yang Cao (Shanghai Jiao Tong University); Wang Changhu (microsoft); Zhang Liqing (Shanghai Jiao Tong University); Lei Zhang (Microsoft Research Asia); | Poster | Image and Video Retrieval |
670 | 769 | Face Image Retrieval by Shape Manipulation | Brandon Smith (University of Wisconsin-Madiso); Shengqi Zhu (University of Wisconsin-Madison); Li Zhang; | Poster | Image and Video Retrieval |
277 | 777 | Hello neighbor: accurate object retrieval with k-reciprocal nearest neighbors | Qin Danfeng (ETH Zurich); Stephan Gammeter (ETH Zurich); Lukas Bossard (ETH Zurich); Till Quack;Luc VanGool; | Poster | Image and Video Retrieval |
857 | 785 | Hierarchical Semantic Indexing for Large Scale Image Retrieval | Jia Deng (Princeton University); Alexander Berg (Stony Brook University); Li Fei-Fei; | Poster | Image and Video Retrieval |
298 | 793 | Image Annotation via Preferential Random Walk on Bi-relational Graph of Images and Semantic Labels | Hua Wang (Univ. of Texas at Arlington); Heng Huang (University of Texas at Arlington, Department of Computer Science and Engineering); Chris Ding; | Poster | Image and Video Retrieval |
84 | 801 | Image Ranking and Retrieval Based on Multi-Attribute Queries | Behjat Siddiquie (University of Maryland); Rogerio Feris;Larry Davis; | Oral | Image and Video Retrieval |
912 | 809 | Image Retrieval with Geometry-Preserving Visual Phrases | Yimeng Zhang (Cornell University); Zhaoyin Jia (Cornell University); Tsuhan Chen; | Oral | Image and Video Retrieval |
502 | 817 | Iterative Quantization: A Procrustean Approach to Learning Binary Codes | Yunchao Gong (UNC Chapel Hill); Svetlana Lazebnik (University of North Carolina at Chapel Hill); | Oral | Image and Video Retrieval |
1113 | 825 | Learning Image Vicept Description via Mixed-Norm Regularization for Large Scale Semantic Image Search | Liang LI (ICT, CAS); Shuqiang Jiang;Qingming Huang (Graduate Univ of Chinese Academy of Sciences); | Poster | Image and Video Retrieval |
300 | 833 | Learning structured prediction models for interactive image labeling | Thomas Mensink (XRCE); Jakob Verbeek;Gabriela Csurka (XRCE); | Poster | Image and Video Retrieval |
297 | 841 | Locality-Sensitive Support Vector Machine by Exploring Local Feature Correlation for Web Image Annotation | Guo-Jun Qi (ECE, UIUC); Qi Tian (University of Texas at San Antonio); Thomas Huang (UIUC); | Poster | Image and Video Retrieval |
45 | 849 | Noise Resistant Graph Ranking for Improved Web Image Search | Wei Liu (Columbia University); Yu-Gang Jiang (Columbia University); Jiebo Luo;Shih-Fu Chang; | Poster | Image and Video Retrieval |
361 | 857 | Query-Specific Visual Semantic Spaces for Web Image Re-ranking | Ke Liu (CUHK); Xiaogang Wang (The Chinese University of Hong Kong); | Poster | Image and Video Retrieval |
734 | 865 | Random Forest Voting for Fast Action Search | Gang YU (Nanyang technological Univ); Junsong Yuan (Nanyang Technological University); Zicheng Liu; | Poster | Image and Video Retrieval |
1795 | 873 | Random Maximum Margin Hashing | Alexis Joly (INRIA); olivier buisson (ina); | Poster | Image and Video Retrieval |
790 | 881 | Tag Localization with Spatial Correlations and Joint Group Sparsity | Yang Yang (The University of Queensland); Yi Yang (The University of Queensland); Zi Huang (The University of Queensland); Heng Tao Shen (The University of Queensland); Feiping Nie (University of Texas, Arlington); | Poster | Image and Video Retrieval |
1288 | 889 | Total Recall II: Query Expansion Revisited | Ondrej Chum;Andrej Mikulik (CMP, CTU in Prague); Michal Perdoch (CMP, CTU in Prague); Jiri Matas; | Poster | Image and Video Retrieval |
22 | 897 | Towards Cross-Cateogory Knowledge Propagation for Learning Visual Concepts | Guo-Jun Qi (ECE, UIUC); Yong Rui (Microsoft Corporation); Qi Tian (University of Texas at San Antonio); Thomas Huang (UIUC); | Oral | Image and Video Retrieval |
1492 | 905 | Unsupervised Auxiliary Visual Words Discovery for Large-Scale Image Object Retrieval | Yin-Hsi Kuo (National Taiwan University and Academia Sinica); Hsuan-Tien Lin;Wen-Huang Cheng;Yi-Hsuan Yang;Winston Hsu; | Poster | Image and Video Retrieval |
104 | 913 | A Complete Statistical Inverse Ray Tracing Approach to Multi-view Stereo | Shubao Liu (Brown University); David Cooper (Brown University); | Poster | Image-Based Modeling |
1452 | 921 | A general method for the Point of Regard estimation in 3D space | Fiora Pirri (Sapienza Università di Roma); Matia Pizzoli (Sapienza Università di Roma); Alessandro Rudi (Sapienza Università di Roma); | Poster | Image-Based Modeling |
1491 | 929 | Active Learning for Piecewise Planar 3D Reconstruction | Adarsh Kowdle (Cornell University); Yao-Jen Chang (Cornell University); Andrew Gallagher;Tsuhan Chen; | Oral | Image-Based Modeling |
1666 | 937 | Adapted Gaussian Models for Image Classification | Mandar Dixit (UC San Diego); Nikhil Rasiwasia (UCSD); Nuno Vasconcelos; | Poster | Image-Based Modeling |
997 | 945 | Capturing Time-of-Flight Data with Confidence | Malcolm Reynolds (University College London); Jozef Doboš (University College London); Leto Peel (BAE Systems); Tim Weyrich (University College London); Gabriel Brostow; | Poster | Image-Based Modeling |
348 | 953 | Extracting Vanishing Points across Multiple Views | Michael Hornacek (VRVis Research Center); Stefan Maierhofer (VRVis); | Poster | Image-Based Modeling |
1748 | 961 | Feature Context for Image Classification and Object Detection | Xinggang Wang (Huazhong Univ. of Sci. & Tech.); Xiang Bai (Huazhong University of Science and Technology); Wenyu Liu (Huazhong University of Science and Technology); LonginJan Latecki; | Poster | Image-Based Modeling |
327 | 969 | High-quality shape from multi-view stereo and shading under general illumination | Chenglei Wu (Max Planck Institut Informatik); Bennett Wilburn;Yasuyuki Matsushita;Christian Theobalt; | Poster | Image-Based Modeling |
364 | 977 | Internal Statistics of a Single Natural Image | Maria Zontak (The Weizmann Institute of Science); Michal Irani; | Oral | Image-Based Modeling |
1383 | 985 | Linearity of Each Channel Pixel Values from a Surface in and out of Shadows and Its Applications | Dong Tian (Sia); dong tang (sia.ac); | Poster | Image-Based Modeling |
1501 | 993 | Reconstruction of relief objects from line drawings | Michael Kolomenkin (Technion); George Leifman (Technion); Ilan Shimshoni;Ayellet Tal (Technion); | Poster | Image-Based Modeling |
1172 | 1001 | Topology-adaptive Multi-view Photometric Stereo | Yusuke Yoshiyasu (Keio University); | Poster | Image-Based Modeling |
713 | 1009 | Translation Symmetry Detection in a Fronto-parallel View | Peng ZHAO (HKUST); Long Quan; | Poster | Image-Based Modeling |
15 | 1017 | A Sobolev-type Metric for Polar Active Contours | Maximilian Baust (CAMP, TU Munich); Anthony J. Yezzi;Gozde Unal (Sabanci University); Nassir Navab (CAMP, TU Munich); | Poster | Medical Image Analysis |
59 | 1025 | Adaptive Shape Composition: A New Framework for Shape Prior Modeling | Shaoting Zhang (Rutgers University); junzhou Huang (Rutgers University, CBIM); Yiqiang Zhan (Siemens); Dimitris Metaxas; | Poster | Medical Image Analysis |
1823 | 1033 | Automated Mitosis Detection of Stem Cell Populations with high confluency in Phase-Contrast Microscopy Images | Seungil Huh (Carnegie Mellon University); Mei Chen (Intel Labs Pittsburgh); | Poster | Medical Image Analysis |
497 | 1041 | CrossTrack: Robust 3D Tracking from Two Cross-Sectional Views | Mohamed Hussein;Fatih Porikli; | Poster | Medical Image Analysis |
219 | 1049 | Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images | Le Lu (Siemens ); Jinbo Bi (University of Connecticut); Matthias Wolf;Marcos Salganicoff; | Poster | Medical Image Analysis |
1052 | 1057 | Feature Guided Motion Artifact Reduction with Structure-Awareness in 4D CT Images | Dongfeng Han (UI); John Bayouth (UI); Qi Song;sudershan Bhatia (UI); Milan Sonka;Xiaodong Wu; | Poster | Medical Image Analysis |
1532 | 1065 | Generalized Group Sparse Classifiers with Application in fMRI Brain Decoding | Bernard Ng;Rafeef Abugharbieh; | Poster | Medical Image Analysis |
1721 | 1073 | Hierarchical Anatomical Brain Networks for MCI Prediction by Partial Least Square Analysis | Luping Zhou (UNC at Chapel Hill, U.S.A); Yaping Wang (Northwestern Polytechnical University, P.R.China); Yang Li (UNC at Chapel Hill, U.S.A); Pew-Thian Yap (UNC at Chapel Hill, U.S.A); Dinggang Shen; | Poster | Medical Image Analysis |
1739 | 1081 | Human Brain Labeling Using Image Similarities | François Rousseau (CNRS); Piotr Habas (UCSF); Colin Studholme (UCSF); | Poster | Medical Image Analysis |
1794 | 1089 | Landmark/Image-based Deformable Registration of Gene Expression Data | Uday Kurkure;Yen Le;Nikos Paragios;James Carson;Tao Ju;Ioannis Kakadiaris; | Poster | Medical Image Analysis |
1013 | 1097 | Learning-based Hypothesis Fusion for Robust Catheter Tracking in 2D X-ray Fluoroscopy | Wen Wu (Siemens Corporate Research); Terrence Chen (Siemens Corporate Research); Adrian Barbu;Peng Wang (Siemens Corporate Research); Norbert Strobel;Shaohua Zhou;Comaniciu Dorin; | Poster | Medical Image Analysis |
1381 | 1105 | Novel 4-D Open-Curve Active Contour and Curve Completion Approach for Automated Tree Structure Extraction | Yu Wang (Rensselaer Polytechnic Inst.); Arunachalam Narayanaswamy (Rensselaer Polytechnic Instituite); Badri Roysam; | Poster | Medical Image Analysis |
307 | 1113 | Regression-Based Label Fusion for Multi-Atlas Segmentation | Hongzhi Wang (University of Pennsylvania); Jung Wook Suh;John Pluta;Murat Altinay;Paul Yushkevich; | Poster | Medical Image Analysis |
1811 | 1121 | Robust Discriminative Wire Structure Modeling with Application to Stent Enhancement in Fluoroscopy | Xiaoguang Lu (Siemens Corporate Research); Terrence Chen (Siemens Corporate Research); Comaniciu Dorin; | Poster | Medical Image Analysis |
1077 | 1129 | sLLE: Spherical Locally Linear Embedding with Applications to Tomography | Yi Fang (Purdue University); S.V.N. Vishwanathan (Purdue University); Mengtian Sun (Purdue University); Karthik Ramani (Purdue University); | Poster | Medical Image Analysis |
1951 | 1137 | A Generative Statistical Model for Tracking Multiple Smooth Trajectories | Ernesto Brau (University of Arizona); Kobus Barnard (Universiy of Arizona); Ravi Palanivelu (University of Arizona); Damayanthi Dunatunga (University of Arizona); Tatsuya Tsukamoto (University of Arizona); Philip Lee; | Poster | Motion and Tracking |
451 | 1145 | A Polar Representation of Motion and Implications for Optical Flow | Yair Adato (Ben Gurion ); Todd Zickler;Ohad Ben-Shahar (Ben-Gurion University); | Poster | Motion and Tracking |
487 | 1153 | A Two-Stage Denoising Approach for Seeing ThroughWater Clearly | Omar Oreifej (University of Central Florida); Guang Shu (University of Central Florida); Teresa Pace (University of Central Florida); Mubarak Shah; | Poster | Motion and Tracking |
1818 | 1161 | Adaptive Metric Differential Tracking | Nan Jiang (HUST); Wenyu Liu (Huazhong University of Science and Technology); Ying Wu (Northwestern University); | Poster | Motion and Tracking |
1279 | 1169 | Branch and Track | Steve Gu (Duke University); Carlo Tomasi; | Poster | Motion and Tracking |
1935 | 1177 | Context Tracker: Exploring Supporters and Distracters in Unconstrained Environments | Thang Dinh (Univ. of Southern California); Gerard Medioni; | Poster | Motion and Tracking |
856 | 1185 | Efficient Track Linking Methods for Track Graphs Using Network-flow and Set-cover Techniques | Zheng Wu (Boston University); Margrit Betke;Thomas Kunz (Boston University); | Poster | Motion and Tracking |
1451 | 1193 | Feature- and Depth-Supported Modified Total Variation Optical Flow for 3D Motion Field Estimation in Real Scenes | Thomas Müller (Daimler Research); Jens Rannacher (Universität Heidelberg); Clemens Rabe (Daimler Research); Uwe Franke (Daimler Research); | Poster | Motion and Tracking |
1297 | 1201 | Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects | Hamed Pirsiavash;Deva Ramanan;Charless Fowlkes (UC Irvine); | Poster | Motion and Tracking |
135 | 1209 | GraphTrack: Faster than Realtime Tracking in Videos | Brian Amberg (University of Basel); Thomas Vetter; | Poster | Motion and Tracking |
310 | 1217 | How does Person Identity Recognition Help Multi-Person Tracking? | Cheng-Hao Kuo (USC); Ram Nevatia; | Poster | Motion and Tracking |
838 | 1225 | Intrinsic Dense 3D Surface Tracking | Yun Zeng;Chaohui Wang (Ecole Centrale Paris/INRIA); Yang Wang;David Gu;Dimitris Samaras;Nikos Paragios; | Oral | Motion and Tracking |
1231 | 1233 | Learning Affinities and Dependencies for Multi-Target Tracking using a CRF Model | Bo Yang (USC); Chang Huang (University of Southern California); Ram Nevatia; | Poster | Motion and Tracking |
541 | 1241 | Learning Temporally Consistent Rigidities | Jean-Sebastien Franco (Grenoble Universities); Edmond Boyer; | Poster | Motion and Tracking |
474 | 1249 | Markerless Motion Capture of Interacting Characters Using Multi-view Image Segmentation | Yebin Liu (Max Planck Institute); Carsten Stoll (Max-Planck-Institut für Informatik); Juergen Gall;Hans-Peter Seidel (MPI Informatik); Christian Theobalt; | Oral | Motion and Tracking |
463 | 1257 | Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection | Xue Mei;Haibin Ling;Yi Wu (Temple University); | Poster | Motion and Tracking |
18 | 1265 | Multi-target Tracking by Continuous Energy Minimization | Anton Andriyenko (TU Darmstadt); Konrad Schindler (ETH Zurich); | Poster | Motion and Tracking |
346 | 1273 | Multiobject Tracking as Maximum Weight Independent Set | William Brendel (Oregon State University); Mohamed Amer (Oregon State University); Sinisa Todorovic; | Oral | Motion and Tracking |
1310 | 1281 | Parsing Human Motion with Structured Ensembles of Stretchable Models | Ben Sapp;David Weiss (University of Pennsylvania); Ben Taskar; | Oral | Motion and Tracking |
932 | 1289 | Probabilistic Simultaneous Pose and Non-Rigid Shape Recovery | Francesc Moreno (Institut de Robotica i Informatica Industrial (UPC/CSIC)); Josep Porta (Institut de Robotica i Informatica Industrial (CSIC-UPC)); | Poster | Motion and Tracking |
47 | 1297 | Real-time Human Pose Recognition in Parts from Single Depth Images | Jamie Shotton (Microsoft Research Cambridge); Andrew Fitzgibbon;Mat Cook;Andrew Blake; | Oral | Motion and Tracking |
714 | 1305 | Real-time visual tracking with compressed sensing | Hanxi Li (ANU); Chunhua Shen (NICTA); Qinfeng Shi (University of Adelaide); | Poster | Motion and Tracking |
1913 | 1313 | Robust Tracking Using Local Sparse Appearance Model and K-Selection | Baiyang Liu (Rutgers University); junzhou Huang (Rutgers University, CBIM); Casimir Kulikowski (Rutgers); Lin Yang (UMDNJ); | Oral | Motion and Tracking |
794 | 1321 | Tracking 3D Human Pose with Large Root Node Uncertainty | Ben Daubney (Swansea); Xianghua Xie (Swansea); | Poster | Motion and Tracking |
968 | 1329 | Tracking Low Resolution Objects by Metric Preservation | Nan Jiang (HUST); Wenyu Liu (Huazhong University of Science and Technology); Ying Wu (Northwestern University); Heng Su (Tsinghua University); | Poster | Motion and Tracking |
1243 | 1337 | Using 3D Scene Structure to Improve Tracking | Jan Prokaj (Univ of Southen California); Gerard Medioni; | Poster | Motion and Tracking |
662 | 1345 | Who are you with and where are you Going? | Kota Yamaguchi (Stony Brook University); Alexander Berg ;Luis Ortiz;Tamara Berg (Stony Brook University); | Poster | Motion and Tracking |
1633 | 1353 | A Coarse-to-fine approach for fast deformable object detection | Marco Pedersoli (Univ. Autònoma de Barcelona); Andrea Vedaldi (Oxford); Jordi Gonzalez (Univ. Autònoma de Barcelona - Computer Vision Center); | Oral | Object Detection |
1393 | 1361 | A Segmentation-aware Object Detection Model with Occlusion Handling | Tianshi Gao (Stanford University); Benjamin Packer;Daphne Koller; | Poster | Object Detection |
235 | 1369 | Adapting an Object Detector by Considering the Worst Case: a Conservative Approach | Guang Chen (University of MIssouri); TonyX. Han; | Poster | Object Detection |
1703 | 1377 | Adaptive Random Forest - How many ``experts'' to ask before making a decision? | Alexander Schwing (ETHZ); Christopher Zach;Yefeng Zheng (Siemens Corporate Research); Marc Pollefeys; | Poster | Object Detection |
1978 | 1385 | Articulated Pose Estimation with Flexible Mixtures-of-Parts | Yi Yang;Deva Ramanan; | Oral | Object Detection |
1682 | 1393 | Boosted Local Structured HOG-LBP for Object Localization | Junge Zhang;Kaiqi Huang (NLPR,CASIA); Tieniu Tan; | Poster | Object Detection |
979 | 1401 | Efficient Region Search for Object Detection | Sudheendra Vijayanarasimhan;Kristen Grauman; | Poster | Object Detection |
209 | 1409 | Efficient Subwindow Search with Submodular Score Functions | Senjian An (Curtin University); Patrick Peursum;Wanquan Liu (curtin university); Svetha Venkatesh; | Poster | Object Detection |
338 | 1417 | Fast and High-Performance Template Matching Method | Alexander Sibiryakov (Mitsubishi Electric); | Poster | Object Detection |
592 | 1425 | Finding the Weakest Link in Person Detectors | Devi Parikh;Larry Zitnick; | Poster | Object Detection |
382 | 1433 | FlowBoost - Appearance Learning from Sparsely Annotated Video | Karim Ali (EPFL); Francois Fleuret (Idiap Research Institute); David Hasler; | Oral | Object Detection |
1238 | 1441 | From Partial Shape Matching through Local Deformation to Robust Global Shape Similarity for Object Detection | Tianyang Ma (Temple University); LonginJan Latecki; | Oral | Object Detection |
498 | 1449 | Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds | Sudheendra Vijayanarasimhan;Kristen Grauman; | Oral | Object Detection |
597 | 1457 | Learning and Matching Multiscale Template Descriptors for Real-Time Detection, Localization and Tracking | Taehee Lee (UCLA); Stefano Soatto; | Poster | Object Detection |
49 | 1465 | Learning Effective Human Pose Estimation from Inaccurate Annotation | Sam Johnson (University of Leeds); Mark Everingham; | Poster | Object Detection |
1140 | 1473 | Learning People Detection Models from Few Training Samples | Leonid Pishchulin (MPI Informatics); Christian Wojek (Max-Planck-Institute Informatics); Arjun Jain;Thorsten Thormaehlen (MPI Informatics); Bernt Schiele (MPI Informatics); | Poster | Object Detection |
1840 | 1481 | Learning to Share Visual Appearance for Multiclass Object Detection | Ruslan Salakhutdinov (MIT); Antonio Torralba;Josh Tenenbaum (MIT); | Poster | Object Detection |
793 | 1489 | PClines - Line Detection Using Parallel Coordinates | Markéta Dubská (Brno University of Technology); Adam Herout (Brno University of Technology); Jiří Havel (Brno University of Technology); | Poster | Object Detection |
428 | 1497 | Proposal Generation for Object Detection using Cascaded Ranking SVMs | Ziming Zhang (Oxford Brookes University); Jonathan Warrell;Philip Torr (Oxford Brookes University); | Poster | Object Detection |
543 | 1505 | Scalable Multi-class Object Detection | Nima Razavi (ETH Zurich); Juergen Gall;Luc VanGool; | Poster | Object Detection |
212 | 1513 | Shared Parts for Deformable Part-based Models | Patrick Ott (University of Leeds); Mark Everingham; | Poster | Object Detection |
168 | 1521 | Unbiased Look at Dataset Bias | Antonio Torralba;Alyosha Efros; | Poster | Object Detection |
77 | 1529 | What Makes a Chair a Chair? | Helmut Grabner;Juergen Gall;Luc VanGool; | Poster | Object Detection |
1430 | 1537 | A Generalized Probabilistic Framework for Compact Codebook Creation | Lingqiao Liu (Australian National University); Lei Wang (Australian National University); Chunhua Shen (NICTA); | Poster | Object Recognition |
24 | 1545 | Are Sparse Representations Really Relevant for Image Classification? | Roberto Rigamonti (EPFL); Matthew Brown (EPFL); Vincent Lepetit; | Poster | Object Recognition |
891 | 1553 | Boundary Preserving Dense Local Regions | Jaechul Kim (University of Texas at Austin); Kristen Grauman; | Oral | Object Recognition |
1456 | 1561 | Classification with Invariant Scattering | Joan Bruna (Ecole Polytechnique); Stéphane Mallat (École Polytechnique); | Poster | Object Recognition |
429 | 1569 | Clues from the Beaten Path: Location Estimation with Bursty Sequences of Tourist Photos | Chao-Yeh Chen (University of Texas at Austin); Kristen Grauman; | Poster | Object Recognition |
254 | 1577 | Combining Randomization and Discrimination for Fine-Grained Image Categorization | Bangpeng Yao (Stanford University); Aditya Khosla;Li Fei-Fei; | Poster | Object Recognition |
86 | 1585 | Contextualizing Object Detection and Classification | Zheng Song (National University of Singapo); Qiang Chen (National Univ. of Singapore); Zhongyang Huang (Panasonic Singapore Laboratories); Yang Hua (PSL); Shuicheng Yan; | Poster | Object Recognition |
926 | 1593 | Deformation and Illumination Invariant Feature Point Descriptor | Francesc Moreno (Institut de Robotica i Informatica Industrial (UPC/CSIC)); | Poster | Object Recognition |
656 | 1601 | Describing Images: Understanding and Generating Image Descriptions | Girish Kulkarni (Stony Brook University); Visruth Premraj (Stony Brook University); Sagnik Dhar (Stony Brook University); Siming Li (Stony Brook University); Alexander Berg ;Yejin Choi (Stony Brook University); Tamara Berg (Stony Brook University); | Oral | Object Recognition |
1766 | 1609 | Discriminative Affine Sparse Codes for Image Classification | Naveen Kulkarni (Student); Baoxin Li; | Poster | Object Recognition |
1728 | 1617 | Discriminative Spatial Pyramid | Tatsuya Harada (The Univ. of Tokyo); Yoshitaka Ushiku (Grad. School of Information Sc); Yuya Yamashita (The Univ. of Tokyo); Yasuo Kuniyoshi (The Univ. of Tokyo); | Poster | Object Recognition |
1506 | 1625 | Efficient Euclidean Distance Transform Using Perpendicular Bisector Segmentation | Jun Wang (Peking University); Ying Tan (Peking University); | Poster | Object Recognition |
324 | 1633 | Establishing Feature Correspondences via Hyper-graph Matching Using Reweighted Random Walks | Jungmin Lee (Seoul National University); Minsu Cho;Kyoung Mu Lee (Seoul National Uniersity); | Poster | Object Recognition |
1422 | 1641 | Exploring Knowledge Transfer and Zero-Shot Learning in a Large-Scale Setting | Marcus Rohrbach (MPI Informatics); Bernt Schiele (MPI Informatics); Michael Stark (MPI Informatics); | Poster | Object Recognition |
1570 | 1649 | Exploring Relations of Visual Codes for Image Classification | yongzhen Huang;Kaiqi Huang (NLPR,CASIA); Tieniu Tan; | Poster | Object Recognition |
660 | 1657 | High Level Describable Attributes for Predicting Aesthetics and Interestingness | Sagnik Dhar (Stony Brook University); Vicente Ordonez (Stony Brook University); Tamara Berg (Stony Brook University); | Poster | Object Recognition |
803 | 1665 | High-Dimensional Signature Compression for Large-Scale Image Classification | Jorge Sanchez (CIII); Florent Perronnin; | Poster | Object Recognition |
715 | 1673 | Image Classification by Non-Negative Sparse Coding, Low-Rank and Sparse Decomposition | Chunjie Zhang (Institute of Automation); Jing Liu;Qi Tian (University of Texas at San Antonio); changsheng Xu;Hanqing Lu;Songde Ma; | Poster | Object Recognition |
593 | 1681 | Interactively Building a Discriminative Vocabulary of Nameable Attributes | Devi Parikh;Kristen Grauman; | Poster | Object Recognition |
694 | 1689 | Large-scale image classification: fast feature extraction and SVM training | Yuanqing Lin (NEC Labs America); Fengjun Lv (NEC Labs America); Shenghuo Zhu (NEC Laboratories America); Ming Yang (NEC Laboratories America); Timothee Cour (NEC Labs America); Kai Yu;Liangliang Cao (UIUC); Thomas Huang (UIUC); | Poster | Object Recognition |
198 | 1697 | Learning A Discriminative Dictionary for Sparse Coding via Label Consistent K-SVD | Zhuolin Jiang (University of Maryland); Zhe Lin (Adobe Systems, Inc.); Larry Davis; | Poster | Object Recognition |
868 | 1705 | Learning Hierarchical Poselets for Human Parsing | Yang Wang;Duan Tran (UIUC); Zicheng Liao (UIUC); | Poster | Object Recognition |
1926 | 1713 | Learning Image Representations from Pixel Level via Hierarchical Sparse Coding | Kai Yu (NEC Labs America); Yuanqing Lin (NEC Labs America); John Lafferty (CMU); | Poster | Object Recognition |
879 | 1721 | Learning the Easy Things First: Self-Paced Visual Category Discovery | Yong Jae Lee (University of Texas at Austin); Kristen Grauman; | Poster | Object Recognition |
1837 | 1729 | Object Recognition with Hierarchical Kernel Descriptors | Liefeng Bo (university of washington); Kevin Lai;Xiaofeng Ren;Dieter Fox; | Poster | Object Recognition |
631 | 1737 | Rank-SIFT: Learning to Rank Local Interest Points | Bing Li (Shanghai JiaoTong Univerisity); Rong Xiao;Zhiwei Li (Microsoft); Rui Cai (Microsoft Research, Asia); Bao-Liang Lu;Lei Zhang (Microsoft Research Asia); | Poster | Object Recognition |
1798 | 1745 | Recognition Using Visual Phrases | Ali Farhadi (UIUC); Mohammad Amin Sadeghi (University of Illinois at Urbana-Champaign); | Oral | Object Recognition |
1691 | 1753 | Salient Coding for Image Classification | yongzhen Huang;Kaiqi Huang (NLPR,CASIA); Tieniu Tan; | Poster | Object Recognition |
975 | 1761 | Sharing Features Between Objects and Their Attributes | Sung Ju Hwang;Fei Sha;Kristen Grauman; | Poster | Object Recognition |
476 | 1769 | Spatial-DiscLDA for Visual Recognition | Zhenxing Niu (Xidian university); Gang Hua (IBM Research T. J. Watson Center); Xinbo Gao;Qi Tian (University of Texas at San Antonio); | Poster | Object Recognition |
683 | 1777 | Visual and Semantic Similarity in ImageNet | Thomas Deselaers (ETH Zurich/Google); Vittorio Ferrari; | Poster | Object Recognition |
1768 | 1785 | What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms | Brian Kulis;Kate Saenko;Trevor Darrell (ICSI, UC Berkeley); | Oral | Object Recognition |
980 | 1793 | Where's Waldo: Matching People in Images of Crowds | Rahul Garg (University of Washington); Deva Ramanan;Steve Seitz;Noah Snavely; | Poster | Object Recognition |
249 | 1801 | A Closed Form Solution to Robust Subspace Estimation and Clustering | Paolo Favaro;René Vidal;Avinash Ravichandran (Johns Hopkins University); | Poster | Optimization Methods |
1240 | 1809 | A Non-convex Relaxation Approach to Sparse Dictionary Learning | Jianping Shi (Zhejiang University); Xiang Ren (Zhejiang University); Jingdong Wang;Guang Dai (ZJU); Zhihua Zhang; | Oral | Optimization Methods |
1549 | 1817 | A Study of Nesterov’s Scheme for Lagrangian Decomposition and MAP Labeling | Bogdan Savchynskyy (Heidelberg University); Jörg Kappes (Heidelberg University); Stefan Schmidt (Heidelberg University); Christoph Schnörr; | Oral | Optimization Methods |
1494 | 1825 | Deterministically Maximizing Feasible Subsystem for Robust Model Fitting with Unit Norm Constraint | Yinqiang Zheng (Tokyo Institute of Technology); Shigeki Sugimoto (Tokyo Institute of Technology); Masatoshi Okutomi; | Poster | Optimization Methods |
1500 | 1833 | Distributed Message Passing for Large Scale Graphical Models | Alexander Schwing (ETHZ); Hazan Tamir;Marc Pollefeys;Raquel Urtasun; | Poster | Optimization Methods |
282 | 1841 | Efficient Training for Pairwise or Higher Order MRFs via Dual Decomposition | Nikos Komodakis; | Poster | Optimization Methods |
1106 | 1849 | Exhaustive Family of Energies Minimizable Exactly by a Graph Cut and Approximations of the Other Ones | Guillaume Charpiat (INRIA); | Poster | Optimization Methods |
596 | 1857 | Inference for Order Reduction in MRFs | Andrew Gallagher;Dhruv Batra;Devi Parikh; | Poster | Optimization Methods |
590 | 1865 | Making the Right Moves: Guiding Alpha-Expansion using Local Primal-Dual Gaps | Dhruv Batra;Pushmeet Kohli; | Poster | Optimization Methods |
1607 | 1873 | Robust Classification via Structured Sparse Representation | Ehsan Elhamifar (Johns Hopkins University); René Vidal; | Poster | Optimization Methods |
461 | 1881 | Scale Invariant cosegmentation for image groups | Lopamudra Mukherjee (Univ of Wisconsin Whitewater); Vikas Singh;Jiming Peng (University of Illinois Urbana Champaign); | Oral | Optimization Methods |
227 | 1889 | Submodular Decomposition Framework for Inference in MRF with Global Constraints | Dmitry Vetrov;Anton Osokin (Moscow State University); Vladimir Kolmogorov; | Poster | Optimization Methods |
1234 | 1897 | Submodularity beyond submodular energies: coupling edges in graph cuts | Stefanie Jegelka (Max Planck Institute); Jeff Bilmes; | Oral | Optimization Methods |
1124 | 1905 | Total Variation for Cyclic Structures | Evgeny Strekalovskiy (Technical University Munich); Daniel Cremers; | Poster | Optimization Methods |
1511 | 1913 | Variable Grouping for Energy Minimization | Taesup Kim (KAIST); Sebastian Nowozin;Pushmeet Kohli;Chang D. Yoo; | Poster | Optimization Methods |
735 | 1921 | Wavelet Belief Propagation for Large Scale Inference Problems | Ruxandra Lasowski (Max Planck Institute Informatik); Art Tevs (Max Planck Institute Informatik); Michael Wand (Max Planck Institute Informatik); Hans-Peter Seidel; | Poster | Optimization Methods |
1343 | 1929 | Evaluating Combinational Color Constancy Methods on Real-World Images | Bing Li (Chinese Academy of Sciences); | Poster | Performance Evaluation |
819 | 1937 | Evaluation of Background Subtraction Techniques for Video Surveillance | Sebastian Brutzer;Benjamin Hoeferlin (University of Stuttgart); Gunther Heidemann (University of Stuttgart); | Poster | Performance Evaluation |
1496 | 1945 | A generative model for 3D urban scene understanding from movable platforms | Andreas Geiger (Karlsruhe Institute of Technology); Martin Lauer (Karlsruhe Institute of Technology); Raquel Urtasun; | Oral | Scene Understanding |
1119 | 1953 | A Hierarchical Conditional Random Field Model for Labeling and Segmenting Images of Street Scenes | Qixing Huang (Stanford University); Mei Han;Bo Wu;Sergey Ioffe; | Poster | Scene Understanding |
586 | 1961 | From 3D Scene Geometry to Human Workspace | Abhinav Gupta;Scott Satkin (CMU); Alyosha Efros;Martial Hebert; | Oral | Scene Understanding |
1210 | 1969 | Functional Categorization of Objects using Real-time Markerless Motion Capture | Juergen Gall;Andrea Fossati;Luc VanGool; | Poster | Scene Understanding |
1967 | 1977 | Heterogeneous Image Features Integration via Multi-View Spectral Clustering | Xiao Cai (Department of Computer Science, University of Texas at Arlington); Feiping Nie (University of Texas, Arlington); Heng Huang (University of Texas at Arlington, Department of Computer Science and Engineering); Farhad Kamangar (Department of Computer Science, University of Texas at Arlington); | Poster | Scene Understanding |
1983 | 1985 | Image analysis by counting on a grid | Alessandro Perina (Microsoft Research); Nebojsa Jojic (Microsoft Research); | Poster | Scene Understanding |
984 | 1993 | Monocular 3D Scene Understanding with Explicit Occlusion Reasoning | Christian Wojek (Max-Planck-Institute Informatics); Stefan Walk (TU Darmstadt); Stefan Roth;Bernt Schiele (MPI Informatics); | Poster | Scene Understanding |
251 | 2001 | Piecing Together the Segmentation Jigsaw using Context | Xi Chen (University of Maryland); Arpit Jain (University of Maryland); Abhinav Gupta;Larry Davis; | Poster | Scene Understanding |
1958 | 2009 | Sampling Bedrooms | Luca Del Pero (University of Arizona); Jinyan Guan (University of Arizona); Ernesto Brau (University of Arizona); Joseph Schlecht (University of Heidelber); Kobus Barnard (Universiy of Arizona); | Poster | Scene Understanding |
73 | 2017 | Scene Shape from Textures of Objects | Nadia Payet (Oregon State University); Sinisa Todorovic; | Poster | Scene Understanding |
632 | 2025 | Semantic structure from motion | Sid Ying-Ze Bao (University of Michigan); Silvio Savarese; | Poster | Scene Understanding |
1868 | 2033 | Single-Image Shadow Detection and Removal using Paired Regions | Ruiqi Guo (UIUC); Qieyun Dai (UIUC); Derek Hoiem (UIUC); | Oral | Scene Understanding |
1313 | 2041 | A Global Optimization Approach to Robust Multi-Model Fitting | Jin Yu (The University of Adelaide); Tat-Jun Chin (The University of Adelaide); David Suter; | Poster | Segmentation and Grouping |
774 | 2049 | A Global Sampling Method for Alpha Matting | Kaiming He (CUHK); Christoph Rhemann (Vienna University of Technolog); Carsten Rother;Xiaoou Tang;Jian Sun; | Poster | Segmentation and Grouping |
1434 | 2057 | Biased Normalized Cuts | Subhransu Maji;Nisheeth Vishnoi (Microsoft Research, India); Jitendra Malik (UC Berkeley); | Poster | Segmentation and Grouping |
1966 | 2065 | Contour cut: identifying salient contours in images by solving a Hermitian eigenvalue problem | Ryan Kennedy (University of Pennsylvania); Jean Gallier;Jianbo Shi; | Poster | Segmentation and Grouping |
250 | 2073 | Detection Free Tracking: Exploiting Motion and Topology for Segmenting and Tracking under Entanglement. | Katerina Fragkiadaki (University of Pennsylvania); Jianbo Shi; | Poster | Segmentation and Grouping |
103 | 2081 | Efficient MCMC Sampling with Implicit Shape Representations | Jason Chang (MIT); John Fisher III (MIT); | Poster | Segmentation and Grouping |
802 | 2089 | Enforcing topological constraints in random field image segmentation | Chao Chen (IST Austria); Daniel Freedman (HP Labs Israel); Christoph Lampert (I.S.T. Austria); | Poster | Segmentation and Grouping |
60 | 2097 | Entropy Rate Superpixel Segmentation | Ming-Yu Liu (Umd.edu,merl.com); Oncel Tuzel (MERL); Srikumar Ramalingam (MERL); Rama Chellappa (UMD); | Poster | Segmentation and Grouping |
345 | 2105 | Foreground Segmentation of Live Videos using Locally Competing 1SVMs | Minglun Gong;Li Cheng (Bioinformatics Institute); | Poster | Segmentation and Grouping |
211 | 2113 | Foreground-Background Segmentation using Iterated Distribution Matching | Viet Pham (University of Tokyo); Keita Takahashi (The University of Tokyo); Takeshi Naemura (The University of Tokyo); | Poster | Segmentation and Grouping |
1325 | 2121 | From Active Contours to Active Surfaces | Akshaya Mishra (Tornado Medical System); Paul Fieguth (University of Waterloo); David Clausi (University of Waterloo); | Poster | Segmentation and Grouping |
437 | 2129 | From Co-saliency to Co-segmentation: An Efficient and Fully Unsupervised Energy Minimization Model | Kai-Yueh Chang (National Tsing Hua University); Tyng-Luh Liu;Shang-Hong Lai (NTHU); | Poster | Segmentation and Grouping |
1687 | 2137 | Graph Connectivity In Sparse Subspace Clustering | Behrooz Nasihatkon (Australian National University); Richard Hartley; | Poster | Segmentation and Grouping |
1747 | 2145 | Heat-Mapping: A Robust Approach Toward Perceptually Consistent Mesh Segmentation | Yi Fang (Purdue University); Mengtian Sun (Purdue University); Karthik Ramani (Purdue University); | Poster | Segmentation and Grouping |
1277 | 2153 | Kernelized Structural SVM Learning for Supervised Object Segmentation | Luca Bertelli (Google); Tianli Yu (Google Inc.); Diem Vu (Google Inc.); Salih Gokturk (Google Inc); | Oral | Segmentation and Grouping |
858 | 2161 | Learning to Find Occlusion Regions | Ahmad Humayun (UCL); Oisin Mac Aodha (UCL); Gabriel Brostow; | Poster | Segmentation and Grouping |
174 | 2169 | Majorization-Minimization mixture model determination in image segmentation | Giorgos Sfikas (University of Strasbourg); Christophoros Nikou (University of Ioannina); Nikos Galatsanos (University of Patras); Christian Heinrich (University of Strasbourg); | Poster | Segmentation and Grouping |
1873 | 2177 | Modelling composite shapes by Gibbs Random Fields | Dmitrij Schlesinger;Boris Flach (Czech technical University Prague); | Poster | Segmentation and Grouping |
1713 | 2185 | Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking | Victor Prisacariu (University of Oxford); Ian Reid (University of Oxford); | Oral | Segmentation and Grouping |
1609 | 2193 | Nonlocal Matting | Philip Lee (Northwestern University); Ying Wu (Northwestern University); | Poster | Segmentation and Grouping |
1734 | 2201 | Nonparametric Density Estimation on A Graph: Learning Framework, Fast Approximation and Application in Image Segmentation | Zhiding Yu (HKUST); Oscar Au (HKUST); Ketan Tang (HKUST); | Poster | Segmentation and Grouping |
1305 | 2209 | O(N) Implicit Subspace Embedding for Unsupervised Multi-scale Image Segmentation | Hongbo Zhou (SIUC); Qiang Cheng (SIUC); | Poster | Segmentation and Grouping |
929 | 2217 | Object Cosegmentation | Sara Vicente (UCL); Carsten Rother;Vladimir Kolmogorov; | Poster | Segmentation and Grouping |
1576 | 2225 | Object Segmentation by Alignment of Poselet Activations to Image Contours | Thomas Brox (Albert-Ludwigs-University Freiburg); Lubomir Bourdev (UC Berkeley); Subhransu Maji;Jitendra Malik (UC Berkeley); | Poster | Segmentation and Grouping |
247 | 2233 | Occlusion Boundary Detection and Figure/Ground Assignment from Optical Flow | Patrik Sundberg (UC Berkeley); Jitendra Malik (UC Berkeley); Michael Maire (California Institute of Technology); Pablo Arbelaez;Thomas Brox (Albert-Ludwigs-University Freiburg); | Oral | Segmentation and Grouping |
169 | 2241 | Partial similarity based nonparametric scene parsing in certain environment | Honghui Zhang (HKUST); Long Quan; | Poster | Segmentation and Grouping |
784 | 2249 | Segment an Image by Looking into an Image Corpus | Xiaobai Liu (Hust.edu.cn); Jiashi Feng (NUS); Shuicheng Yan;Hai Jin (hust.edu.cn); | Poster | Segmentation and Grouping |
1280 | 2257 | Semi-Supervised Video Segmentation | Ignas Budvytis (Cambridge University); Vijay Badrinarayanan;Roberto Cipolla (Cambridge University); | Poster | Segmentation and Grouping |
1316 | 2265 | Shape Based Pedestrian Parsing | Yihang Bo (Beijing Jiaotong University, Beijing,China); Charless Fowlkes (UC Irvine); | Poster | Segmentation and Grouping |
51 | 2273 | Shape Grammar Parsing via Reinforcement Learning | Olivier Teboul (Ecole Centrale Paris); Iasonas Kokkinos;Panagiotis Koutsourakis (Ecole Centrale Paris); Loic Simon (ECP); Nikos Paragios; | Poster | Segmentation and Grouping |
1518 | 2281 | Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation | Alex Shyr (UC Berkeley); Trevor Darrell (ICSI, UC Berkeley); Michael Jordan (UC Berkeley); Raquel Urtasun; | Poster | Segmentation and Grouping |
875 | 2289 | Supervised Hypergraph Labeling | Toufiq Parag;Ahmed Elgammal; | Poster | Segmentation and Grouping |
475 | 2297 | Time and Space Efficient Spectral Clustering via Column Sampling | Mu Li (Shanghai Jiao Tong University); Xiao-Chen Lian;James Kwok (HKUST); Bao-Liang Lu; | Poster | Segmentation and Grouping |
822 | 2305 | Unsing Ripley's K-function to Improve Graph-Based Clustering Techniques | Kevin Streib (Ohio State University); Jim Davis; | Poster | Segmentation and Grouping |
665 | 2313 | Using Global Bag of Features Models in Random Fields for Joint Categorization and Segmentation of Objects | Dheeraj Singaraju;René Vidal; | Poster | Segmentation and Grouping |
989 | 2321 | Camera Calibration with Lens Distortion from Low-rank Textures | Zhengdong Zhang (Microsoft Research Asi); Yasuyuki Matsushita;Yi Ma; | Poster | Sensors |
618 | 2329 | High-resolution Hyperspectral Imaging via Matrix Factorization | Rei Kawakami;John Wright;Yu-Wing Tai (KAIST); Yasuyuki Matsushita;Moshe Ben-Ezra (Microsoft Research Asia); Katsushi Ikeuchi; | Poster | Sensors |
408 | 2337 | Radiometric Calibration by Transform Invariant Low-rank Structure | Joon-Young Lee (KAIST); Boxin Shi (The University of Tokyo); Yasuyuki Matsushita;InSo Kweon;Katsushi Ikeuchi; | Poster | Sensors |
1232 | 2345 | 2D Nonrigid Partial Shape Matching Using MCMC and Contour Subdivision | Yu Cao (University of South Carolina); Zhiqi Zhang (University of South Carolina); Irina Czogiel (Max Planck Institute for Molecular Genetics); Ian Dryden (University of South Carolina); Song Wang; | Poster | Shape Representation and Matching |
499 | 2353 | A Deformation and Lighting Insensitive Metric for Face Recognition Based on Dense Correspondences | Anne Jorstad (University of Maryland); David Jacobs;Alain Trouvé (Ecole Normale Superieure de Cachan); | Poster | Shape Representation and Matching |
725 | 2361 | Affine-invariant diffusion geometry for the analysis of deformable 3D shapes | Dan Raviv (Technion); Alexander Bronstein (Dept. of Electrical Engineering, Tel Aviv University, Israel); Michael Bronstein (University of Lugano); Ron Kimmel (Technion - IIT); Nir Sochen; | Poster | Shape Representation and Matching |
72 | 2369 | Affinity Learning on a Tensor Product Graph with Applications to Shape and Image Retrieval | Xingwei Yang (Temple University); LonginJan Latecki; | Poster | Shape Representation and Matching |
311 | 2377 | Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor | Bin Fan;Fuchao Wu;Zhanyi Hu; | Poster | Shape Representation and Matching |
521 | 2385 | Contour Based Joint Clustering of Multiple Segmentations | Daniel Glasner (Weizmann Institute of Science); Shiv Vitaladevuni (Raytheon BBN Technologies); Ronen Basri; | Oral | Shape Representation and Matching |
155 | 2393 | Discriminative Image Warping with Attribute Flow | Weiyu Zhang (University of Pennsylvania); Praveen Srinivasan;Jianbo Shi; | Poster | Shape Representation and Matching |
1446 | 2401 | Efficient Groupwise Non-rigid Registration of Textured Surfaces | Kirill Sidorov (Cardiff University); Stephen Richmond (Cardiff University); David Marshall (Cardiff University); | Poster | Shape Representation and Matching |
1680 | 2409 | Global Optimization for Optimal Generalized Procrustes Analysis | Daniel Pizarro (University of Alcala); Adrien Bartoli (Université d'Auvergne); | Poster | Shape Representation and Matching |
1211 | 2417 | Graph Matching through Entropic Manifold Alignment | Francisco Escolano (University of Alicante); Edwin Hancock;Miguel Lozano (University of Alicante); | Poster | Shape Representation and Matching |
1021 | 2425 | Matching 2D Image Lines to 3D Models: Two Improvements and a New Algorithm | Behzad Kamgar-Parsi (ONR); | Poster | Shape Representation and Matching |
1859 | 2433 | Multi-Level Inference by Relaxed Dual Decomposition for Human Pose Segmentation | Huayan Wang (Stanford University); Daphne Koller; | Poster | Shape Representation and Matching |
1103 | 2441 | Multiview Registration via Graph Diffusion of Dual Quaternions | Andrea Torsello;Emanuele Rodola (Università Ca' Foscari Venezia); Andrea Albarelli; | Poster | Shape Representation and Matching |
116 | 2449 | Optimal Similarity Registration of Volumetric Images | Effrosyni Kokiopoulou (ETH Zurich); Michail Zervos (University of Athens, Department of Informatics and Telecommunications); Daniel Kressner (ETH Zurich, Seminar for Applied Mathematics); Nikos Paragios; | Poster | Shape Representation and Matching |
426 | 2457 | Registration for 3D Surfaces with Large Deformations Using Quasi-Conformal Curvature Flow | Wei Zeng (Stony Brook University); David Gu; | Poster | Shape Representation and Matching |
2002 | 2465 | Robust Point Set Registration Using EM-ICP with Information-Theoretically Optimal Outlier Handling | Jeroen Hermans (Katholieke Universiteit Leuven); Dirk Smeets;Paul Suetens (K.U.Leuven); Dirk Vandermeulen; | Poster | Shape Representation and Matching |
1200 | 2473 | Scale and Rotation Invariant Matching Using Linearly Augmented Trees | Hao Jiang (Boston College); Tai-Peng Tian (Boston University); Stan Sclaroff (Boston University); | Oral | Shape Representation and Matching |
605 | 2481 | Topologically-Robust 3D Shape Matching Based on Diffusion Geometry and Seed Growing | Avinash Sharma (INRIA); Radu Horaud;Jan Cech (INRIA); Edmond Boyer; | Poster | Shape Representation and Matching |
1323 | 2489 | 2.5D Building Modeling with Topology Control | Qian-Yi Zhou (USC); Ulrich Neumann (USC); | Poster | Shape-from-X |
741 | 2497 | A pattern framework driven by the Hamming distance for structured light-based reconstruction with a single image | Xavier Maurice (Univsersity of Strasbourg); | Poster | Shape-from-X |
1294 | 2505 | A Theory of Differential Photometric Stereo for General Isotropic BRDFs | Jiamin Bai (UC Berkeley); Manmohan Chandraker (UC Berkeley); Ravi Ramamoorthi (UC Berkeley); | Oral | Shape-from-X |
678 | 2513 | Adequate Reconstruction of Transparent Objects on a Shoestring Budget | Sai-Kit Yeung (UCLA); Tai-Pang Wu;Chi-keung Tang;Tony F. Chan (HKUST); Stanley Osher (UCLA); | Poster | Shape-from-X |
339 | 2521 | High-Frequency Shape and Albedo from Shading using Natural Image Statistics | Jonathan Barron (UC Berkeley); Jitendra Malik (UC Berkeley); | Poster | Shape-from-X |
478 | 2529 | Least Squares Surface Reconstruction from Gradients: Direct Algebraic Methods with Spectral, Tikhonov, and Constrained Regularization | Matthew Harker (University of Leoben); Paul O'Leary (University of Leoben); | Poster | Shape-from-X |
164 | 2537 | Multiview Specular Stereo Reconstruction of Large Mirror Surfaces | Jonathan Balzer (KAUST); Sebastian Hoefer;Juergen Beyerer; | Poster | Shape-from-X |
287 | 2545 | Recovering Shape from a Single Image of a Mirrored Surface from Curvature Constraints | Marshall Tappen (UCF); | Poster | Shape-from-X |
827 | 2553 | Shape Estimation in Natural Illumination | Micah Johnson;Edward Adelson (MIT); | Poster | Shape-from-X |
1598 | 2561 | Shape from Specular Flow: Is One Flow Enough? | Yuriy Vasilyev (Harvard University); Todd Zickler;Steven Gortler (Harvard University); Ohad Ben-Shahar (Ben-Gurion University); | Poster | Shape-from-X |
1260 | 2569 | Structure from motion blur in low light | Yali Zheng (Chongqing University); Shohei NOBUHARA (Kyoto University); Yaser Sheikh; | Poster | Shape-from-X |
390 | 2577 | Symmetric Piecewise Planar Object Reconstruction from a Single Image | Tianfan XUE (IE Department, CUHK); Jianzhuang LIU (CUHK); | Poster | Shape-from-X |
1015 | 2585 | A Direct Formulation for Totally-corrective Multi-class Boosting | Chunhua Shen (NICTA); Zhihui Hao (Beijing Institute of Technology); | Poster | Statistical Methods and Learning |
2021 | 2593 | A Probabilistic Representation for Efficient Large Scale Visual Recognition Tasks | Subhabrata Bhattacharya (UCF); Rahul Sukthankar;Rong Jin (Michigan State University); Mubarak Shah (UCF); | Poster | Statistical Methods and Learning |
578 | 2601 | A Scalable Dual Approach to Semidefinite Metric Learning | Chunhua Shen (NICTA); Junae Kim (Australian National University); Lei Wang (Australian National University); | Poster | Statistical Methods and Learning |
260 | 2609 | Accelerated Low-Rank Visual Recovery by Random Projection | Yadong Mu, Jian Dong, Xiaotong Yuan, Shuicheng Yan | Oral | Statistical Methods and Learning |
240 | 2617 | AdaBoost on Low-Rank PSD Matrices for Metric Learning with Applications in Computer Aided Diagnosis | Jinbo Bi (University of Connecticut); Dijia Wu;Le Lu (Siemens ); Meizhu Liu;Yimo Tao;Matthias Wolf; | Poster | Statistical Methods and Learning |
1560 | 2625 | Bayesian Deblurring with Integrated Noise Estimation | Uwe Schmidt (TU Darmstadt); Kevin Schelten (TU Darmstadt); Stefan Roth; | Poster | Statistical Methods and Learning |
1380 | 2633 | Comparing Data-Dependent and Data-Independent Embeddings for Classification and Ranking of Internet Images | Yunchao Gong (UNC Chapel Hill); Svetlana Lazebnik (University of North Carolina at Chapel Hill); | Poster | Statistical Methods and Learning |
788 | 2641 | Connecting Non-Quadratic Variational Models and MRFs | Kevin Schelten (TU Darmstadt); Stefan Roth; | Poster | Statistical Methods and Learning |
1814 | 2649 | Dynamic Batch Mode Active Learning | Shayok Chakraborty (Arizona State University); Vineeth Balasubramanian (Arizona State University); Sethuraman Panchanathan (Arizona State University); | Poster | Statistical Methods and Learning |
13 | 2657 | Efficient approximations to the marginal likelihood in blind deconvolution | Anat Levin (Weizmann Institute of Science); Yair Weiss;Bill Freeman;Fredo Durand (MIT); | Poster | Statistical Methods and Learning |
892 | 2665 | From Region Similarity to Category Discovery | Carolina Galleguillos (U.C San Diego); Brian McFee (U.C San Diego); Serge Belongie (UCSD); Gert Lanckriet (U.C San Diego); | Poster | Statistical Methods and Learning |
407 | 2673 | Gated Classifiers: Boosting under High Intra-Class Variation | Oscar Danielsson (KTH); Babak Rasolzadeh (KTH); Stefan Carlsson (KTH); | Poster | Statistical Methods and Learning |
1716 | 2681 | Generalized Gaussian Process Models | Antoni Chan (City University of Hong Kong); Daxiang Dong (Hong Kong University of Science and Technology); | Poster | Statistical Methods and Learning |
854 | 2689 | Generalized Projection Based M-Estimator: Theory and Applications | Sushil Mittal (Rutgers University); Saket Anand (Rutgers University); Peter Meer (Rutgers University); | Poster | Statistical Methods and Learning |
263 | 2697 | Geometric $\ell_p$-norm Feature Pooling for Image Classification | Jiashi Feng (NUS); Bingbing Ni;Qi Tian (University of Texas at San Antonio); Shuicheng Yan; | Poster | Statistical Methods and Learning |
1088 | 2705 | Graph Embedding Discriminant Analysis on Grassmannian Manifolds for Improved Image Set Matching | Mehrtash Harandi (NICTA); Sareh Shirazi (National ICT Australia (NICTA)); Conrad Sanderson (National ICT Australia (NICTA)); Brian Lovell; | Poster | Statistical Methods and Learning |
1215 | 2713 | Hybrid Generative-Discriminative Classification using Posterior Divergence | Xiong Li (Shanghai Jiao Tong University); Tai Sing Lee (Department of Computer Science, Carnegie Mellon University); Yuncai Liu (Department of Automation, Shanghai Jiao Tong University); | Poster | Statistical Methods and Learning |
1529 | 2721 | Learning Better Image Representations Using `Flobject Analysis' | Inmar Givoni (University of Toronto); Patrick Li (University of Toronto); Brendan Frey (University of Toronto); | Poster | Statistical Methods and Learning |
969 | 2729 | Learning invariance through imitation | Graham Taylor;Ian Spiro (New York University); Rob Fergus;Christoph Bregler (NYU); | Poster | Statistical Methods and Learning |
1867 | 2737 | Learning Message-Passing Inference Machines for Structured Prediction | Stephane Ross (Carnegie Mellon University); Daniel Munoz (Carnegie Mellon University); J. Andrew Bagnell (Carnegie Mellon University); | Poster | Statistical Methods and Learning |
873 | 2745 | Learning Non-Local Range Markov Random Field for Image Restoration | Jian Sun (Xi'an Jiaotong University); Marshall Tappen; | Poster | Statistical Methods and Learning |
686 | 2753 | Learning Transformation Invariant Representations from weakly-related Videos | Christian Leistner (icg tugraz); Martin Godec;Samuel Schulter;Manuel Werlberger;Amir Saffari;Horst Bischof; | Poster | Statistical Methods and Learning |
1705 | 2761 | Local Isomorphism to Solve the Pre-image Problem in Kernel Methods | Dong Huang (Carnegie Mellon University); Yuandong Tian (Carnegie Mellon University); Fernando DelaTorre; | Poster | Statistical Methods and Learning |
722 | 2769 | Max-margin Clustering: Detecting Margins from Projections of Points on Lines | Raghuraman Gopalan (University of Maryland); Jagan Sankaranarayanan; | Poster | Statistical Methods and Learning |
692 | 2777 | Mining Discriminative Co-occurrence Patterns for Visual Recognition | Junsong Yuan (Nanyang Technological University); Ming Yang (NEC Laboratories America); Ying Wu (Northwestern University); | Poster | Statistical Methods and Learning |
1574 | 2785 | MKPM: a multiclass extension of the Kernel Projection Machine | Sylvain Takerkart (CNRS); Liva Ralaivola (LIF); | Poster | Statistical Methods and Learning |
973 | 2793 | Modeling the joint density of two images under a variety of transformations | Joshua Susskind (University of Toronto); Roland Memisevic;Geoffrey Hinton (University of Toronto); Marc Pollefeys; | Poster | Statistical Methods and Learning |
1940 | 2801 | Multi-label Learning with Incomplete Class Assignments | Serhat Bucak (Michigan State University); Rong Jin (Michigan State University); Anil Jain (Michigan State University); | Poster | Statistical Methods and Learning |
599 | 2809 | Multi-layer Group Sparse Coding -- for Concurrent Image Classification and Annotation | Shenghua Gao (Nanyang Technological Univ.); Liang-Tien Chia (Nanyang Technological University); Ivor W. Tsang; | Poster | Statistical Methods and Learning |
352 | 2817 | Multifactor Analysis Based on Factor-Dependent Geometry | Sung Won Park (Carnegie Mellon University); | Poster | Statistical Methods and Learning |
1620 | 2825 | Multiscale Geometric and Spectral Analysis of Plane Arrangements | Guangliang Chen (Duke University); Mauro Maggioni; | Poster | Statistical Methods and Learning |
14 | 2833 | Natural Image Denoising: Optimality and Inherent Bounds | Anat Levin (Weizmann Institute of Science); Boaz Nadler (Weizmann Inst of Science); | Poster | Statistical Methods and Learning |
748 | 2841 | Non-negative Matrix Factorization as a Feature Selection Tool for Maximum Margin Classifiers | Mithun Gupta (GE); Jing Xiao (Epson R&D); | Poster | Statistical Methods and Learning |
732 | 2849 | Nonnegative Sparse Coding for Discriminative Semi-supervised Learning | Ran He (Institute of Automation Chines); Wei-Shi Zheng (Queen Mary University of London); | Poster | Statistical Methods and Learning |
1797 | 2857 | On Deep Generative Models with Applications to Recognition | Marc'Aurelio Ranzato;Joshua Susskind (University of Toronto); Volodymyr Mnih (University of Toronto); Geoffrey Hinton (University of Toronto); | Poster | Statistical Methods and Learning |
1799 | 2865 | Online Group-Structured Dictionary Learning | Zoltan Szabo (Eotvos Lorand University); Barnabas Poczos (Carnegie Mellon University); Andras Lorincz (Eotvos Lorand University); | Poster | Statistical Methods and Learning |
954 | 2873 | Particle Filter with State Permutations for Solving Image Jigsaw Puzzles | Xingwei Yang (Temple University); Nagesh Adluru;LonginJan Latecki; | Poster | Statistical Methods and Learning |
1379 | 2881 | Principal Regression Analysis | Jason Saragih (CSIRO); | Oral | Statistical Methods and Learning |
80 | 2889 | Recovery of Corrupted Low-Rank Matrices via Half-Quadratic based Nonconvex Minimization | Ran He (Institute of Automation Chines); zhenan sun ( Institute of Automation Chinese Academy of Sciences); Tieniu Tan;Wei-Shi Zheng (Queen Mary University of London); | Poster | Statistical Methods and Learning |
1712 | 2897 | Robust and Efficient Regularized Boosting Using Total Bregman Divergence | Meizhu Liu (University of Florida); Baba Vemuri; | Poster | Statistical Methods and Learning |
337 | 2905 | Sparse Concept Coding for Visual Analysis | Deng Cai;Xiaofei He; | Poster | Statistical Methods and Learning |
1464 | 2913 | Sparse Image Representation with Epitomes | Louise Benoit (ENS); Julien Mairal;Francis Bach (INRIA); Jean Ponce; | Poster | Statistical Methods and Learning |
1697 | 2921 | Supervised Local Subspace Learning for Continuous Head Pose Estimation | Dong Huang (Carnegie Mellon University); Markus Storer (Graz University of Technology ); Fernando DelaTorre;Horst Bischof; | Poster | Statistical Methods and Learning |
1298 | 2929 | TaylorBoost: First and Second-order Boosting Algorithms with Explicit Margin Control | Mohammad Saberian (UC San Diego); Hamed Masnadi-Shirazi (UC San Diego); Nuno Vasconcelos; | Poster | Statistical Methods and Learning |
55 | 2937 | Truncated Message Passing | Justin Domke; | Poster | Statistical Methods and Learning |
127 | 2945 | Visual textures as realizations of multivariate log-Gaussian Cox processes | Huu-Giao Nguyen (Telecom Bretgane); Ronan Fablet (Institut Telecom / Telecom Bretagne); Jean-Marc Boucher (Institut Telecom / Telecom Bretagne); | Poster | Statistical Methods and Learning |
185 | 2953 | A Branch and Contract Algorithm For Globally Optimal Fundamental Matrix Estimation | Yinqiang Zheng (Tokyo Institute of Technology); Shigeki Sugimoto (Tokyo Institute of Technology); Masatoshi Okutomi; | Poster | Stereo and Structure from Motion |
1635 | 2961 | A Brute-Force Algorithm for Reconstructing a Scene from Two Projections | Olof Enqvist (Lund University); Fangyuan Jiang (Lund University); Fredrik Kahl; | Poster | Stereo and Structure from Motion |
642 | 2969 | A Novel Parametrization of the Perspective-Three-Point Problem for a Direct Computation of Absolute Camera Position and Orientation | Laurent Kneip (ETH Zurich); Davide Scaramuzza;Roland Siegwart (ETH Zurich); | Poster | Stereo and Structure from Motion |
112 | 2977 | A Robust Method for Vector Field Learning with Application to Mismatch Removing | Ji Zhao (Huazhong Univ of Sci & Tech); Ma Jiayi; | Poster | Stereo and Structure from Motion |
962 | 2985 | An Analysis of Using High-Frequency Sinusoidal Illumination to Measure the 3D Shape of Translucent Objects | Michael Holroyd (University of Virginia); Jason Lawrence (University of Virginia); | Poster | Stereo and Structure from Motion |
1270 | 2993 | Analytical Projection Model for Non-Central Catadioptric Cameras with Quadric Mirrors | Amit Agrawal;Yuichi Taguchi (Mitsubishi Electric Research Labs); Srikumar Ramalingam (MERL); | Oral | Stereo and Structure from Motion |
1420 | 3001 | Discrete-Continuous Optimization for Large-scale Structure from Motion | David Crandall (Indiana University); Andrew Owens (MIT); Noah Snavely;Daniel Huttenlocher; | Oral | Stereo and Structure from Motion |
308 | 3009 | Energy Based Multiple Model Fitting for Non-Rigid Structure from Motion | Chris Russell;Joao Fayad (Queen Mary, UoL); Lourdes Agapito; | Poster | Stereo and Structure from Motion |
276 | 3017 | Fast Cost-Volume Filtering for Visual Correspondence and Beyond | Christoph Rhemann (Vienna University of Technolog); Asmaa Hosni (Vienna University of Technology); Michael Bleyer (Vienna University of Technology); Carsten Rother;margrit Gelautz (Vienna University of Technology); | Poster | Stereo and Structure from Motion |
615 | 3025 | Fusion of GPS and Structure-from-Motion using Constrained Bundle Adjustments | Maxime Lhuillier; | Poster | Stereo and Structure from Motion |
700 | 3033 | Global Stereo Matching Leveraged by Sparse Ground Control Points | Liang Wang;Ruigang Yang (University of Kentucky); | Poster | Stereo and Structure from Motion |
2006 | 3041 | L1-rotation averaging using the Weiszfeld algorithm | Richard Hartley (ANU); | Poster | Stereo and Structure from Motion |
830 | 3049 | Line-Based Relative Pose Estimation | Ali Elqursh (Rutgers University); Ahmed Elgammal; | Poster | Stereo and Structure from Motion |
1010 | 3057 | Multicore Bundle Adjustment | Changchang Wu (University of Washington at Se); Changchang Wu (University of Washtingon at Seattle); Sameer Agarwal;Brian Curless (University of Washtingon at Seattle); Steve Seitz; | Poster | Stereo and Structure from Motion |
1043 | 3065 | Non-Rigid Structure from Motion with Complementary Rank-3 Spaces | Paulo Gotardo (The Ohio State University); Aleix Martinez; | Poster | Stereo and Structure from Motion |
216 | 3073 | NonLinear Refinement of Structure from Motion Reconstruction by Taking Advantage of a Partial Knowledge of the Environment | Mohamed Tamaazousti (CEA LIST); Vincent Gay-Bellile;Sylvie Naudet Colette (CEA LIST); steve bourgeois;michel dhome; | Poster | Stereo and Structure from Motion |
1205 | 3081 | Object Stereo - Joint Stereo Matching and Object Segmentation | Michael Bleyer (Vienna University of Technology); Carsten Rother;Pushmeet Kohli;Daniel Scharstein;Sudipta Sinha; | Poster | Stereo and Structure from Motion |
938 | 3089 | Projective Alignment of Range and Parallax Data | Miles Hansard (INRIA Rhone-Alpes); Radu Horaud;Michel Amat (INRIA Rhone-Alpes); Seungkyu Lee (SAIT); | Poster | Stereo and Structure from Motion |
1112 | 3097 | Reduced Epipolar Cost for Accelerated Incremental SfM | Antonio Rodríguez (Universidad de Murcia); Pedro Enrique López-De-Teruel (University of Murcia); Alberto Ruiz (University of Murcia); | Poster | Stereo and Structure from Motion |
942 | 3105 | Relative pose problem for non-overlapping surveillance cameras with known gravity vector | Branislav Micusik; | Poster | Stereo and Structure from Motion |
1009 | 3113 | Repetition-based Dense Single-View Reconstruction | Changchang Wu (University of Washington at Se); Changchang Wu (University of Washtingon at Seattle); Jan-Michael Frahm;Marc Pollefeys; | Poster | Stereo and Structure from Motion |
1738 | 3121 | Robust, Accurate and Weakly-Supported-Surfaces preserving Multi-View Reconstruction | Michal Jancosek (CTU Prague); Tomas Pajdla (CTU Prague); | Poster | Stereo and Structure from Motion |
553 | 3129 | Scene Flow Estimation by Growing Correspondence Seeds | Jan Cech (INRIA); Jordi Sanchez-Riera (INRIA); Radu Horaud; | Poster | Stereo and Structure from Motion |
991 | 3137 | Structure from motion for scenes with large duplicate structures | Richard Roberts (Georgia Institute of Technology); Sudipta Sinha;Richard Szeliski;Drew Steedly; | Poster | Stereo and Structure from Motion |
1788 | 3145 | The Light-Path Less Traveled | Srikumar Ramalingam (MERL); Sofien Bouaziz (EPFL); Peter Sturm;Philip Torr (Oxford Brookes University); | Poster | Stereo and Structure from Motion |
1230 | 3153 | A Large-scale Benchmark Dataset for Event Recognition in Surveillance Video | Sangmin Oh;Anthony Hoogs;A.G.Amitha Perera;Chia-Chih Chen (UT ECE); Jong Taek Lee (The University of Texas at Austin); Jake Aggarwal;Hyungtae Lee (University of Maryland, College Park); Larry Davis;Xiaoyang Wang (Rensselaer Polytechnic Institute); Eran Swears (RPI); Qiang Ji;Kishore Reddy (University Of Central Florida); Mubarak Shah;Carl Vondrick (University of California, Irvi); Hamed Pirsiavash;Deva Ramanan;Jenny Yuen (MIT); Antonio Torralba;Bi Song (UCR); Anesco Fong (Univ. of California, Riverside); Amit Roy-Chowdhury;Mita Desai (DARPA); | Poster | Video Analysis and Event Recognition |
1031 | 3161 | Abnormal Detection Using Interaction Energy Potentials | Xinyi Cui (Rutgers University); Qingshan Liu (Rutgers University); Mingchen Gao (Rutgers University); Dimitris Metaxas; | Poster | Video Analysis and Event Recognition |
405 | 3169 | action recognition by dense trajectories | Heng Wang (Chinese Academy of Sciences); Alexander Kläser;Cordelia Schmid;Cheng-Lin Liu (CASIA); | Poster | Video Analysis and Event Recognition |
1435 | 3177 | Action Recognition from a Distributed Representation of Pose and Appearance | Subhransu Maji;Lubomir Bourdev (UC Berkeley); Jitendra Malik (UC Berkeley); | Poster | Video Analysis and Event Recognition |
750 | 3185 | Action Recognition with Multiscale Spatio-Temporal Contexts | Jiang Wang (Northwestern University); Zhuoyuan Chen (Northwestern University); Ying Wu (Northwestern University); | Poster | Video Analysis and Event Recognition |
1646 | 3193 | Activity Recognition using Dynamic Subspace Angles | Octavia Camps;Mario Sznaier (Northeastern University); Binlong Li (Northeastern University); Teresa Mao (Northeastern University); Mustafa Ayazoglu (Northeastern University); | Poster | Video Analysis and Event Recognition |
1513 | 3201 | Actom Sequence Models for Efficient Action Detection | Adrien Gaidon (INRIA); Harchaoui Zaid;Cordelia Schmid; | Poster | Video Analysis and Event Recognition |
1890 | 3209 | Cross-View Action Recognition via View Knowledge Transfer | Jingen Liu (UMich); Mubarak Shah;Benjamin Kuipers;Silvio Savarese; | Oral | Video Analysis and Event Recognition |
376 | 3217 | Discriminative Tag Learning on YouTube Videos with Latent Sub-tags | Weilong Yang (Simon Fraser University); George Toderici (Google Inc.); | Poster | Video Analysis and Event Recognition |
1187 | 3225 | Earth Mover’s Prototypes: a Convex Learning Approach for Discovering Activity Patterns in Dynamic Scenes | Elisa Ricci (Fondazione Bruno Kessler); Gloria Zen (Fondazione Bruno Kessler); | Oral | Video Analysis and Event Recognition |
1120 | 3233 | Extracting and Locating Temporal Motifs in Video Scenes Using a Hierarchical Non Parametric Bayesian Model | Rémi Emonet (Idiap); Jagannadan Varadarajan (Idiap); Jean-Marc Odobez (Idiap); | Poster | Video Analysis and Event Recognition |
395 | 3241 | Fast Unsupervised Ego-Action Learning for First-person Sports Videos | Kris Kitani (UCSD); Yoichi Sato;Takahiro Okabe;Akihiro Sugimoto (NII); | Poster | Video Analysis and Event Recognition |
1062 | 3249 | Identifying Players in Broadcast Sports Videos using Conditional Random Fields | Wei-Lwun Lu (University of British Columbia); Jo-Anne Ting (University of British Columbia); Kevin Murphy;Jim Little; | Poster | Video Analysis and Event Recognition |
295 | 3257 | Instantly Telling What Happens in a Video Sequence Using Light Features | Liang Wang (Harbin Institute of Technology); Yizhou Wang;Tingting Jiang (School of EECS, Peking University); Wen Gao (Peking University); | Poster | Video Analysis and Event Recognition |
666 | 3265 | Joint Segmentation and Classification of Human Actions in Video | MinhHoai Nguyen;Zhen-zhong Lan (Carnegie Mellon University); Fernando DelaTorre; | Poster | Video Analysis and Event Recognition |
1790 | 3273 | Learning Context for Collective Activity Recognition | Wongun Choi (University of Michigan); Silvio Savarese;Khuram Shahid; | Poster | Video Analysis and Event Recognition |
568 | 3281 | Learning to Recognize Objects in Egocentric Activities | Alireza Fathi (Georgia Institute of Technolog); Xiaofeng Ren;James Rehg; | Poster | Video Analysis and Event Recognition |
314 | 3289 | Multi-agent event recognition in structured scenarios | Vlad Morariu (University of Maryland); Larry Davis; | Poster | Video Analysis and Event Recognition |
1918 | 3297 | Novelty detection from an Ego-centric perspective | Omid Aghazadeh (KTH); Josephine Sullivan;Stefan Carlsson; | Poster | Video Analysis and Event Recognition |
1725 | 3305 | On Dynamic Scene Geometry for View-invariant Action Matching | Anwaar Haq (Monash); Iqbal Gondal (Monash University); Mubarak Shah (UCF); | Poster | Video Analysis and Event Recognition |
883 | 3313 | Online Detection of Unusual Events in Videos via Dynamic Sparse Coding | Bin Zhao (Carnegie Mellon University); Li Fei-Fei;Eric Xing; | Poster | Video Analysis and Event Recognition |
438 | 3321 | Optimal Spatio-Temporal Path Discovery for Video Event Detection and Localization | Du Tran (NTU); Junsong Yuan (Nanyang Technological University); | Poster | Video Analysis and Event Recognition |
746 | 3329 | Probabilistic Event Logic for Interval-Based and Holistic Event Recognition | William Brendel (Oregon State University); Alan Fern (Oregon State University); Sinisa Todorovic; | Poster | Video Analysis and Event Recognition |
189 | 3337 | Recognizing Human Actions by Attributes | Jingen Liu (UMich); Benjamin Kuipers;Silvio Savarese; | Oral | Video Analysis and Event Recognition |
515 | 3345 | Scenario-Based Video Event Recognition by Constraint Flow | Suha Kwak (POSTECH); Bohyung Han (POSTECH); Joon Han (POSTECH); | Poster | Video Analysis and Event Recognition |
220 | 3353 | Space-Time Super-Resolution from a Single Video | Oded Shahar (The Weizmann Institute of Science); Alon Faktor (The Weizmann Institute of Science); Michal Irani; | Oral | Video Analysis and Event Recognition |
783 | 3361 | Stacked Convolutional Independent Subspace Analysis for Action Recognition | Quoc Le (Stanford University); Will Zou (Stanford University ); Serena Yeung (Stanford University); Andrew Ng (Stanford University); | Oral | Video Analysis and Event Recognition |
1756 | 3369 | Track to the future: Spatio-temporal video segmentation with long-range motion cues | José Lezama (INRIA); Karteek Alahari (ENS / INRIA - WILLOW); Josef Sivic (INRIA / Ecole Normale Superieure); Ivan Laptev; | Poster | Video Analysis and Event Recognition |
1690 | 3377 | TVParser: An Automatic TV Video Parsing Method | Chao Liang (Chinese Academy of Sciences); changsheng Xu;Jian Cheng;Hanqing Lu; | Poster | Video Analysis and Event Recognition |
1761 | 3385 | A 3-D Marked Point Process Model for Multi-View People Detection | Ákos Utasi (MTA SZTAKI); Csaba Benedek (MTA SZTAKI); | Poster | Video Surveillance |
1573 | 3393 | A Novel Supervised Level Set Method for Non-Rigid Object Tracking | Xin Sun (Harbin Institute of Technology); Hongxun Yao;Shengping Zhang (Harbin Institute of Technology); | Poster | Video Surveillance |
1760 | 3401 | Automatic Adaptation of a Generic Pedestrian Detector to a Specific Traffic Scene | Meng Wang (The Chinese University of HK); Xiaogang Wang (The Chinese University of Hong Kong); | Poster | Video Surveillance |
439 | 3409 | Continuously Tracking and See-through Occlusion Based on A New Hybrid Synthetic Aperture Imaging Model | Tao Yang (Nrothwestern Polytechnic Univ.); Yanning Zhang (NWPU); Xiaomin Tong (School of Computer Science, Northwestern Polytechnical University); Xiaoqiang Zhang (School of Computer Science, Northwestern Polytechnical University); Rui Yu (School of Computer Science, Northwestern Polytechnical University); | Poster | Video Surveillance |
1866 | 3417 | Dirichlet Process Mixture Models on Symmetric Positive Definite Matrices for Appearance Clustering in Video Surveillance Applications | Anoop Cherian (University of Minnesota); Vassilios Morellas (University of Minnesota, Twin Cities); Nikolaos Papanikolopoulos; | Poster | Video Surveillance |
1017 | 3425 | Modeling Human Activities as Speech | Chia-Chih Chen (UT ECE); Jake Aggarwal; | Poster | Video Surveillance |
353 | 3433 | Object Association Across PTZ Cameras using Logistic MIL | Karthik Sankaranarayanan (Ohio State University); Jim Davis; | Poster | Video Surveillance |
628 | 3441 | Random Field Topic Model for Semantic Region Analysis in Crowded Scenes from Tracklets | Bolei Zhou (CUHK); Xiaogang Wang (The Chinese University of Hong Kong); | Poster | Video Surveillance |
512 | 3449 | Sparse Reconstruction Cost for Abnormal Event Detection | Yang Cong (Nanyang Technological of Unive); Junsong Yuan (Nanyang Technological University); Ji Liu (University of Wisconsin–Madison); | Poster | Video Surveillance |
1632 | 3457 | Stable Multi-Target Tracking in Real-Time Surveillance Video | Ben Benfold (University of Oxford); Ian Reid (University of Oxford); | Oral | Video Surveillance |
1170 | 3465 | Vehicle Tracking Across Nonoverlapping Cameras Using Joint Kinematic and Appearance Features | Bogdan Matei;Harpreet Sawhney (SRI International Sarnoff); Supun Samarasekera (Sarnoff Corporation); | Poster | Video Surveillance |
533 | 3473 | Global temporal registration of multiple non-rigid surface sequences | Peng Huang (University of Surrey); Adrian Hilton;Chris Budd (University of Surrey); | Poster | Vision for Graphics |
814 | 3481 | High Quality Intrinsic Images Using Optimization | Jianbing Shen (Beijing Institute ofTechnology); Xiaoshan Yang (Beijing Institute of Technology); | Poster | Vision for Graphics |
828 | 3489 | Online Environment Mapping | Jongwoo Lim;Jan-Michael Frahm;Marc Pollefeys; | Poster | Vision for Robotics |
1431 | 3497 | Structure-from-Motion Based Hand-Eye Calibration Using $L_{\infty}$ Minimization | Jan Heller (CTU in Prague); Michal Havlena (CTU in Prague); Tomas Pajdla (CTU Prague); Akihiro Sugimoto (NII); | Poster | Vision for Robotics |