Optimization with graph cuts became very popular in recent years. Progress in problems such as stereo correspondence, image segmentation, etc., can be attributed, in part, to the ...
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Graph cuts methods are at the core of many state-of-theart algorithms in computer vision due to their efficiency in computing globally optimal solutions. In this paper, we solve t...
Illumination changes are a ubiquitous problem in computer vision. They present a challenge in many applications, including tracking: for example, an object may move in and out of ...
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...