In this paper, we use large neighborhood Markov random fields to learn rich prior models of color images. Our approach extends the monochromatic Fields of Experts model (Roth &...
Alex J. Smola, Julian John McAuley, Matthias O. Fr...
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
: Contour Estimation, Bayesian Estimation, Random Fields, Dynamic Programming, Multigrid Methods. This paper addresses contour estimation on images modeled as piecewise homogeneous...
Generative topic models such as LDA are limited by their inability to utilize nontrivial input features to enhance their performance, and many topic models assume that topic assig...