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CVPR
2009
IEEE
16 years 9 months ago
Alphabet SOUP: A Framework for Approximate Energy Minimization
Many problems in computer vision can be modeled using conditional Markov random fields (CRF). Since finding the maximum a posteriori (MAP) solution in such models is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
CVPR
2009
IEEE
16 years 9 months ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...
ICCV
2009
IEEE
16 years 6 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
142
Voted
CVPR
1996
IEEE
16 years 3 months ago
Determining Correspondences and Rigid Motion of 3-D Point Sets with Missing Data
This paper addresses the general 3-D rigid motion problem, where the point correspondences and the motion parameters between two sets of 3-D points are to be recovered. The existe...
Xiaoguang Wang, Yong-Qing Cheng, Robert T. Collins...
112
Voted
CVPR
2001
IEEE
16 years 3 months ago
Tracking of Object with SVM Regression
This paper presents a novel feature-matching based approach for rigid object tracking. The proposed method models the tracking problem as discovering the affine transforms of obje...
Weiyu Zhu, Song Wang, Ruei-Sung Lin, Stephen E. Le...