We provide Ising formulations for many NP-complete and NP-hard problems, including all of
Karp's 21 NP-complete problems. This collects and extends mappings to the Ising model …

In recent years the unconstrained binary quadratic program (UBQP) has grown in
importance in the field of combinatorial optimization due to its application potential and its …

State-of-the-art research on MRFs, successful MRF applications, and advanced topics for
future study. This volume demonstrates the power of the Markov random field (MRF) in …

In this paper we present a new approach for establishing correspondences between sparse
image features related by an unknown non-rigid mapping and corrupted by clutter and …

In this paper, we present a comprehensive survey of Markov Random Fields (MRFs) in
computer vision and image understanding, with respect to the modeling, the inference and …

Second-order priors on the smoothness of 3D surfaces are a better model of typical scenes
than first-order priors. However, stereo reconstruction using global inference algorithms …

Many computer vision applications rely on the efficient optimization of challenging, so-called
non-submodular, binary pairwise MRFs. A promising graph cut based approach for …

Light fields are image-based representations that use densely sampled rays as a scene
description. In this paper, we explore geometric structures of 3D lines in ray space for …

The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple
discrete or continuous labels remains an open question. In this paper, we demonstrate one …

We introduce a transformation of general higher-order Markov random field with binary
labels into a first-order one that has the same minima as the original. Moreover, we formalize …