Abstract. We propose an algorithmic framework for computing global solutions of variational models with convex regularity terms that permit quite arbitrary data terms. While the mi...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
Segmentation of motion in an image sequence is one of the most challenging problems in image processing, while at the same time one that finds numerous applications. To date, a wea...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
In this paper, a primal dual method for general possible nonconvex nonlinear optimization problems is considered. The method is an exterior point type method which means that it p...
Abstract. We propose a vector representation approach to contour estimation from noisy data. Images are modeled as random elds composed of a set of homogeneous regions contours (bo...