MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves

Jörg Hendrik Kappes, Thorsten Beier, Christoph Schnörr

Abstract: Many computer vision problems can be cast into optimization problems over discrete graphical models also known as Markov or conditional random fields. Standard methods are able to solve those problems quite efficiently. However, problems with huge label spaces and or higher-order structure remain challenging or intractable even for approximate methods.