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Poselets: Body Part Detectors trained Using 3D Human Pose Annotations Lubomir Bourdev & Jitendra Malik ICCV 2009
Computer Vision Group UC Berkeley Object detection by multi-scale scanning Ask this question repeatedly, varying position, scale, category… Paradigm introduced by Rowley, Baluja & Kanade 96 for face detection. Viola & Jones 01, Dalal & Triggs 05, Felzenszwalb, McAllester, Ramanan 08
Computer Vision Group UC Berkeley Object detection by multi-scale scanning Ask this question repeatedly, varying position, scale, category… Paradigm introduced by Rowley, Baluja & Kanade 96 for face detection Viola & Jones 01, Dalal & Triggs 05, Felzenszwalb, McAllester, Ramanan 08
PASCAL VOC 2009 Detection
Challenges Sub-categories Aspects Occlusion Addressed by Poselets (Bourdev & Malik, 09)
PASCAL VOC 2009 Average Precision (the best)
Segmentation Results on PASCAL VOC 2009 (w/ Subhransu Maji)
Computer Vision Group UC Berkeley How should we combine high level and low level knowledge? Jitendra Malik UC Berkeley Recognition using regions is joint.
Classification using intersection kernel SVMs is efficient Joint work with Subhransu Maji and Alex Berg (CVPR08) Jitendra Malik UC Berkeley.
- Pictorial Structures for Object Recognition Pedro F. Felzenszwalb & Daniel P. Huttenlocher - A Discriminatively Trained, Multiscale, Deformable Part.
Learning Semantics with Less Supervision. Agenda Beyond Fixed Keypoints Beyond Keypoints Open discussion.
Max-Margin Additive Classifiers for Detection Subhransu Maji & Alexander Berg University of California at Berkeley Columbia University ICCV 2009, Kyoto,
Semantic Contours from Inverse Detectors Bharath Hariharan et.al. (ICCV-11)
Shape Matching and Object Recognition using Low Distortion Correspondence Alexander C. Berg, Tamara L. Berg, Jitendra Malik U.C. Berkeley.
Weakly supervised learning of MRF models for image region labeling Jakob Verbeek LEAR team, INRIA Rhône-Alpes.
Are Categories Necessary in a Data-Rich World? Alexei (Alyosha) Efros CMU Joint work with Tomasz Malisiewicz.
Latent SVMs for Human Detection with a Locally Affine Deformation Field Ľubor Ladický 1 Phil Torr 2 Andrew Zisserman 1 1 University of Oxford 2 Oxford.
Efficient Image Scene Analysis and Applications24/04/20141/46 Efficient Image Scene Analysis and Applications Ming-Ming Cheng Torr Vision Group, Oxford.
Real-Time Detection, Alignment and Recognition of Human Faces Rogerio Schmidt Feris Pattern Recognition Project June 12, 2003.
1 Hierarchical Part-Based Human Body Pose Estimation * Ramanan Navaratnam * Arasanathan Thayananthan Prof. Phil Torr * Prof. Roberto Cipolla * University.
Attributes for Classifier Feedback Amar Parkash and Devi Parikh.
Shane Kinsella th year Electronic Engineering 4BN1 NUI Galway Supervisor: Peter Corcoran March 2009.
Object recognition (part 2) CSE P 576 Larry Zitnick
Putting Objects in Perspective Derek Hoiem Alexei A. Efros Martial Hebert Carnegie Mellon University Robotics Institute.
1 Human Gesture Recognition by Mohamed Bécha Kaâniche 11/02/2009.
Coherent Laplacian 3D protrusion segmentation Oxford Brookes Vision Group Queen Mary, University of London, 11/12/2009 Fabio Cuzzolin.
Regionlets for Generic Object Detection Xiaoyu Wang, Ming Yang, Shenghuo Zhu, and Yuanqing Lin NEC Labs America, Inc. Facebook, Inc. ICCV 2013 oral paper.
1 Recognition by Association: ask not “What is it?” ask “What is it like?” Tomasz Malisiewicz and Alyosha Efros CMU CVPR’08.
Object recognition (part 1) CSE P 576 Larry Zitnick
Statistical Learning of Multi-View Face Detection Microsoft Research Asia Stan Li, Long Zhu, Zhen Qiu Zhang, Andrew Blake, Hong Jiang Zhang, Harry Shum.
Lectureship Early Career Fellowship School of Technology, Oxford Brookes University 19/6/2008 Fabio Cuzzolin INRIA Rhone-Alpes.
CVPR2013 Poster Modeling Actions through State Changes.
Feature Detection. Description Localization More Points Robust to occlusion Works with less texture More Repeatable Robust detection Precise localization.
Course Overview What is AI? What are the Major Challenges? What are the Main Techniques? Where are we failing, and why? Step back and look at.
Describing Images Using Attributes. Describing Images Farhadi et.al. CVPR 2009.
O BJ C UT M. Pawan Kumar Philip Torr Andrew Zisserman UNIVERSITY OF OXFORD.
3D Model Matching with Viewpoint-Invariant Patches(VIP) Reporter ：鄒嘉恆 Date ： 10/06/2009.
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