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» Learning bilinear models for two-factor problems in vision
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ICML
2008
IEEE
14 years 11 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
CVPR
2009
IEEE
15 years 5 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...
ECCV
2010
Springer
14 years 3 months ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
ICMCS
2005
IEEE
110views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Learned color constancy from local correspondences
The ability of humans for color constancy, i.e. the ability to correct for color deviation caused by a different illumination, is far beyond computer vision performances: nowadays...
Tijmen Moerland, Frédéric Jurie
CVPR
2000
IEEE
15 years 5 days ago
Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian Networks
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...