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» Markov Random Fields with Efficient Approximations
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CVPR
2008
IEEE
14 years 9 months ago
Visibility in bad weather from a single image
Bad weather, such as fog and haze, can significantly degrade the visibility of a scene. Optically, this is due to the substantial presence of particles in the atmosphere that abso...
Robby T. Tan
ICCV
2009
IEEE
15 years 14 days ago
Higher-Order Gradient Descent by Fusion-Move Graph Cut
Markov Random Field is now ubiquitous in many formulations of various vision problems. Recently, optimization of higher-order potentials became practical using higherorder graph...
Hiroshi Ishikawa
CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
ECCV
2006
Springer
14 years 9 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 2 months ago
Beyond Pairwise Energies: Efficient Optimization for Higher-order MRFs
In this paper, we introduce a higher-order MRF optimization framework. On the one hand, it is very general; we thus use it to derive a generic optimizer that can be applied to a...
Nikos Komodakis (University of Crete), Nikos Parag...