This paper presents Bayesian edge inference (BEI), a
single-frame super-resolution method explicitly grounded in
Bayesian inference that addresses issues common to existing
meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
We propose a method to identify and localize object
classes in images. Instead of operating at the pixel level,
we advocate the use of superpixels as the basic unit of a
class s...
Markov Random Field is now ubiquitous in many formulations
of various vision problems. Recently, optimization
of higher-order potentials became practical using higherorder
graph...
In the task of visual object categorization, semantic context can play the very important role of reducing ambiguity in objects' visual appearance. In this work we propose to...
Andrew Rabinovich, Andrea Vedaldi, Carolina Galleg...
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...