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» Markov Random Field Modeling in Computer Vision
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CVPR
2011
IEEE
13 years 22 days ago
A Hierarchical Conditional Random Field Model for Labeling and Segmenting Images of Street Scenes
Simultaneously segmenting and labeling images is a fundamental problem in Computer Vision. In this paper, we introduce a hierarchical CRF model to deal with the problem of labelin...
Qixing Huang, Mei Han, Bo Wu, Sergey Ioffe
PAMI
2007
123views more  PAMI 2007»
13 years 8 months ago
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields
—Recent developments in statistical theory and associated computational techniques have opened new avenues for image modeling as well as for image segmentation techniques. Thus, ...
Dalila Benboudjema, Wojciech Pieczynski
ICPR
2006
IEEE
14 years 3 months ago
A Conditional Random Field Model for Video Super-resolution
In this paper, we propose a learning-based method for video super-resolution. There are two main contributions of the proposed method. First, information from cameras with differe...
Dan Kong, Mei Han, Wei Xu, Hai Tao, Yihong Gong
CVPR
2008
IEEE
14 years 11 months ago
The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling
Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...
CVPR
2008
IEEE
14 years 11 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