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» A Method for Localization by Integration of Imprecise Vision...
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ICPR
2008
IEEE
14 years 2 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...
ECCV
2010
Springer
14 years 1 months ago
Randomized Locality Sensitive Vocabularies for Bag-of-Features Model
Abstract. Visual vocabulary construction is an integral part of the popular Bag-of-Features (BOF) model. When visual data scale up (in terms of the dimensionality of features or/an...
CVPR
2006
IEEE
14 years 9 months ago
Training Deformable Models for Localization
We present a new method for training deformable models. Assume that we have training images where part locations have been labeled. Typically, one fits a model by maximizing the l...
Deva Ramanan, Cristian Sminchisescu
ACCV
2010
Springer
13 years 2 months ago
MRF Labeling for Multi-view Range Image Integration
Multi-view range image integration focuses on producing a single reasonable 3D point cloud from multiple 2.5D range images for the reconstruction of a watertight manifold surface. ...
Ran Song, Yonghuai Liu, Ralph R. Martin, Paul L. R...
ECCV
2008
Springer
14 years 9 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher