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» Markov Random Field Modeling in Computer Vision
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ICCV
2007
IEEE
14 years 3 months ago
Action Recognition from Arbitrary Views using 3D Exemplars
In this paper, we address the problem of learning compact, view-independent, realistic 3D models of human actions recorded with multiple cameras, for the purpose of recognizing th...
Daniel Weinland, Edmond Boyer, Rémi Ronfard
CVPR
2007
IEEE
14 years 11 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
ICASSP
2011
IEEE
13 years 24 days ago
Powerful extensions to CRFS for grapheme to phoneme conversion
Conditional Random Fields (CRFs) have proven to perform well on natural language processing tasks like name transliteration, concept tagging or grapheme-to-phoneme (g2p) conversio...
Stefan Hahn, Patrick Lehnen, Hermann Ney
CVPR
2007
IEEE
14 years 11 months ago
A Multi-Resolution Dynamic Model for Face Aging Simulation
In this paper we present a dynamic model for simulating face aging process. We adopt a high resolution grammatical face model[1] and augment it with age and hair features. This mo...
Jin-Li Suo, Feng Min, Song Chun Zhu, Shiguang Shan...
CVPR
2004
IEEE
14 years 11 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic