In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
—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 p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...
— This paper studies automatic image classification by modeling soft-assignment in the popular codebook model. The codebook model describes an image as a bag of discrete visual ...
Jan van Gemert, Cor J. Veenman, Arnold W. M. Smeul...
—In this paper, we present novel techniques that improve the computational and memory efficiency of algorithms for solving multi-label energy functions arising from discrete MRF...
Karteek Alahari, Pushmeet Kohli, Philip H. S. Torr