The quest for a vision system capable of representing and recognizing arbitrary motions benefits from a low dimensional, non-specific representation of flow fields, to be used in ...
This paper is focused on the Co-segmentation problem
[1] – where the objective is to segment a similar object from
a pair of images. The background in the two images may be
ar...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
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...
This paper presents a nonparametric approach to labeling
of local image regions that is inspired by recent developments
in information-theoretic denoising. The chief novelty
of ...