Orals 2A Object Detection - 10:30-12:10 Ballroom 1 |
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); |
FlowBoost - Appearance Learning from Sparsely Annotated Video |
Karim Ali (EPFL); Francois Fleuret (Idiap Research Institute); David Hasler; |
Articulated Pose Estimation with Flexible Mixtures-of-Parts |
Yi Yang;Deva Ramanan; |
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds |
Sudheendra Vijayanarasimhan;Kristen Grauman; |
From Partial Shape Matching through Local Deformation to Robust Global Shape Similarity for Object Detection |
Tianyang Ma (Temple University); LonginJan Latecki; |
Orals 2B - Optimization Methods - 10:30-12:10 Ballroom 2 |
A Non-convex Relaxation Approach to Sparse Dictionary Learning |
Jianping Shi (Zhejiang University); Xiang Ren (Zhejiang University); Jingdong Wang;Guang Dai (ZJU); Zhihua Zhang; |
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; |
Scale Invariant cosegmentation for image groups |
Lopamudra Mukherjee (Univ of Wisconsin Whitewater); Vikas Singh;Jiming Peng (University of Illinois Urbana Champaign); |
Submodularity beyond submodular energies: coupling edges in graph cuts |
Stefanie Jegelka (Max Planck Institute); Jeff Bilmes; |
Scale and Rotation Invariant Matching Using Linearly Augmented Trees |
Hao Jiang (Boston College); Tai-Peng Tian (Boston University); Stan Sclaroff (Boston University); |
Orals 2C - Segmentation and Grouping - 3:30 -5:10 Ballroom 1
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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); |
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking |
Victor Prisacariu (University of Oxford); Ian Reid (University of Oxford); |
Kernelized Structural SVM Learning for Supervised Object Segmentation |
Luca Bertelli (Google); Tianli Yu (Google Inc.); Diem Vu (Google Inc.); Salih Gokturk (Google Inc); |
Contour Based Joint Clustering of Multiple Segmentations |
Daniel Glasner (Weizmann Institute of Science); Shiv Vitaladevuni (Raytheon BBN Technologies); Ronen Basri; |
Real-time Human Pose Recognition in Parts from Single Depth Images |
Jamie Shotton (Microsoft Research Cambridge); Andrew Fitzgibbon;Mat Cook;Andrew Blake; |
Orals 2D - Motion and Tracking - 3:30-5:10 Ballroom 2 |
Multiobject Tracking as Maximum Weight Independent Set |
William Brendel (Oregon State University); Mohamed Amer (Oregon State University); Sinisa Todorovic; |
Parsing Human Motion with Structured Ensembles of Stretchable Models |
Ben Sapp;David Weiss (University of Pennsylvania); Ben Taskar; |
Intrinsic Dense 3D Surface Tracking |
Yun Zeng;Chaohui Wang (Ecole Centrale Paris/INRIA); Yang Wang;David Gu;Dimitris Samaras;Nikos Paragios; |
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); |
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; |