This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Many structured information extraction tasks employ collective graphical models that capture interinstance associativity by coupling them with various clique potentials. We propos...
We propose a novel solid/fluid coupling method that treats the coupled system in a fully implicit manner making it stable for arbitrary time steps, large density ratios, etc. In c...
Avi Robinson-Mosher, Tamar Shinar, Jon Gretarsson,...
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the problem using a number of di...
Ben Glocker, Nikos Paragios, Nikos Komodakis, Geor...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...