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» Computational Probabilistic Non-interference
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139
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ICCV
2003
IEEE
16 years 5 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
ICCV
2001
IEEE
16 years 5 months ago
Human Tracking with Mixtures of Trees
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
Sergey Ioffe, David A. Forsyth
123
Voted
ICCV
2001
IEEE
16 years 5 months ago
A Co-inference Approach to Robust Visual Tracking
Visual trackan,g cou,ld be treeted as a param,eter estim.ation. problem, of target representastionbased on observations in im,age sequ.ences. A rich,er target represen,tation, wou...
Ying Wu, Thomas S. Huang
ICCV
2001
IEEE
16 years 5 months ago
Joint Feature Distributions for Image Correspondence
We introduce `Joint Feature Distributions', a general statistical framework for feature based multi-image matching that explicitly models the joint probability distributions ...
Bill Triggs
ECCV
2008
Springer
16 years 5 months ago
Unsupervised Learning of Skeletons from Motion
Abstract. Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to le...
David A. Ross, Daniel Tarlow, Richard S. Zemel