The saddle point framework provides a convenient way to formulate many convex variational problems that occur in computer vision. The framework unifies a broad range of data and re...
Jan Lellmann, Dirk Breitenreicher, Christoph Schn&...
In this work we propose a convex relaxation approach
for computing minimal partitions. Our approach is based
on rewriting the minimal partition problem (also known as
Potts mode...
Thomas Pock (Graz University of Technology), Anton...
This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This nonlocal graph allows to adapt the penalization to t...
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...