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» Synchronous Random Fields and Image Restoration
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TIT
2008
90views more  TIT 2008»
14 years 9 months ago
Scanning and Sequential Decision Making for Multidimensional Data - Part II: The Noisy Case
We consider the problem of sequential decision making for random fields corrupted by noise. In this scenario, the decision maker observes a noisy version of the data, yet judged wi...
Asaf Cohen, Tsachy Weissman, Neri Merhav
PAMI
2007
176views more  PAMI 2007»
14 years 9 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
103
Voted
CVPR
2009
IEEE
16 years 4 months ago
Higher-Order Clique Reduction in Binary Graph Cut
We introduce a new technique that can reduce any higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, w...
Hiroshi Ishikawa 0002
CVPR
2010
IEEE
15 years 6 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
ECCV
2006
Springer
15 years 11 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady