Relaxation-Based Preprocessing Techniques for Markov Random Field Inference

CVPR 2016 Chen WangRamin Zabih

Markov Random Fields (MRFs) are a widely used graphical model, but the inference problem is NP-hard. For first-order MRFs with binary labels, Dead End Elimination (DEE) and QPBO can find the optimal labeling for some variables; the much harder case of larger label sets has been addressed by Kovtun and related methods which impose substantial computational overhead... (read more)

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