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» Multiscale Conditional Random Fields for Image Labeling
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CVPR
2009
IEEE
15 years 3 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
IJCV
2011
152views more  IJCV 2011»
13 years 3 months ago
Recovering Occlusion Boundaries from an Image
Occlusion reasoning is a fundamental problem in computer vision. In this paper, we propose an algorithm to recover the occlusion boundaries and depth ordering of free-standing str...
Derek Hoiem, Alexei A. Efros, Martial Hebert
CVPR
2004
IEEE
14 years 10 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
PAMI
2011
12 years 11 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
SIAMIS
2010
102views more  SIAMIS 2010»
13 years 3 months ago
Cross Correlation and Deconvolution of Noise Signals in Randomly Layered Media
It is known that cross correlation of waves generated by noise sources, propagating in an unknown medium, and recorded by a sensor array, can provide information about the medium. ...
Josselin Garnier, Knut Sølna