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ICPR
2006
IEEE
15 years 6 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
2010
IEEE
15 years 5 months ago
A Novel Markov Random Field Based Deformable Model for Face Recognition
In this paper, a new scheme to address the face recognition problem is proposed. Different from traditional face recognition approaches which represent each facial image by a sing...
Shu Liao, Albert C.S. Chung
ECAI
2006
Springer
15 years 4 months ago
Polynomial Conditional Random Fields for Signal Processing
We describe Polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex...
Trinh Minh Tri Do, Thierry Artières
120
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JMLR
2008
159views more  JMLR 2008»
15 years 10 days ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
CVPR
2011
IEEE
14 years 4 months 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