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...
We introduce a linearly weighted variant of the total
variation for vector fields in order to formulate regularizers
for multi-class labeling problems with non-trivial interclass...
We propose a convex variational framework to compute high resolution images from a low resolution video. The image formation process is analyzed to provide to a well designed model...
Markus Unger, Thomas Pock, Manuel Werlberger, Hors...
We present a methodology for off-chip memory bandwidth minimization through application-driven L2 cache partitioning in multicore systems. A major challenge with multi-core system...
We present a practical, stratified autocalibration algorithm with theoretical guarantees of global optimality. Given a projective reconstruction, the first stage of the algorithm ...