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105
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JMLR
2010
191views more  JMLR 2010»
14 years 9 months ago
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
Michael Gutmann, Aapo Hyvärinen
133
Voted
CVPR
2010
IEEE
15 years 11 months ago
A Generative Perspective on MRFs in Low-Level Vision
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
Uwe Schmidt, Qi Gao, Stefan Roth
123
Voted
AAAI
2008
15 years 5 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
CVPR
2005
IEEE
16 years 4 months ago
Estimating Disparity and Occlusions in Stereo Video Sequences
We propose an algorithm for estimating disparity and occlusion in stereo video sequences. The algorithm defines a prior on sequences of disparity maps using a 3D Markov random fie...
Oliver M. C. Williams, Michael Isard, John MacCorm...
113
Voted
CVPR
2006
IEEE
15 years 8 months ago
Combined Depth and Outlier Estimation in Multi-View Stereo
In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes:...
Christoph Strecha, Rik Fransens, Luc J. Van Gool