In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
In this paper we study the following problem: given two source images A and A , and a target image B, can we learn to synthesize a new image B which relates to B in the same way t...