Many solutions to computer vision and image processing problems involve the minimization of multi-label energy functions with up to K variables in each term. In the minimization pr...
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
In this paper, we address the stereo matching problem in the presence of reflections and translucency, where image formation can be modeled as the additive superposition of layers...
Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear...
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...