On learning higher-order consistency potentials for multi-class pixel labeling

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Park, Kyoungup
Gould, Stephen

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Springer

Abstract

Pairwise Markov random fields are an effective framework for solving many pixel labeling problems in computer vision. However, their performance is limited by their inability to capture higher-order correlations. Recently proposed higher-order models are

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Restricted until

2037-12-31