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ECCV
2006
Springer
14 years 8 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
CVPR
2009
IEEE
15 years 1 months ago
Efficient Planar Graph Cuts with Applications in Computer Vision
We present a fast graph cut algorithm for planar graphs. It is based on the graph theoretical work [2] and leads to an efficient method that we apply on shape matching and im- a...
Daniel Cremers, Eno Töppe, Frank R. Schmidt
CVPR
2010
IEEE
13 years 8 months ago
A Study on Continuous Max-Flow and Min-Cut Approaches
Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...
Jing Yuan, Egil Bae, Xuecheng Tai
CP
2005
Springer
13 years 11 months ago
Speeding Up Constrained Path Solvers with a Reachability Propagator
Constrained path problems have to do with finding paths in graphs subject to constraints. One way of constraining the graph is by enforcing reachability on nodes. For instance, i...
Luis Quesada, Peter Van Roy, Yves Deville
COLING
2008
13 years 7 months ago
The Power of Negative Thinking: Exploiting Label Disagreement in the Min-cut Classification Framework
Treating classification as seeking minimum cuts in the appropriate graph has proven effective in a number of applications. The power of this approach lies in its ability to incorp...
Mohit Bansal, Claire Cardie, Lillian Lee