The max-sum labeling problem, defined as maximizing a sum of binary (ie, pairwise)
functions of discrete variables, is a general NP-hard optimization problem with many …

The problem of efficient, interactive foreground/background segmentation in still images is of
great practical importance in image editing. Classical image segmentation tools use either …

Several new algorithms for visual correspondence based on graph cuts have recently been
developed. While these methods give very strong results in practice, they do not handle …

State-of-the-art stereo vision algorithms utilize color changes as important cues for object
boundaries. Most methods impose heuristic restrictions or priors on disparities, for example …

We address the problem of computing the 3-dimensional shape of an arbitrary scene from a
set of images taken at known viewpoints. Multi-camera scene reconstruction is a natural …

Top-down visual saliency is an important module of visual attention. In this work, we propose
a novel top-down saliency model that jointly learns a Conditional Random Field (CRF) and a …

As light is transmitted from subject to observer it is absorbed and scattered by the medium it
passes through. In mediums with large suspended particles, such as fog or turbid water, the …

In this manuscript, we offer a gentle review of submodularity and supermodularity and their
properties. We offer a plethora of submodular definitions; a full description of a number of …

In this paper, we address the problem of shadow detection and removal from single images
of natural scenes. Differently from traditional methods that explore pixel or edge information …

Recent stereo algorithms have achieved impressive results by modelling the disparity image
as a Markov Random Field (MRF). An important component of an MRF-based approach is …