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» Object recognition and Random Image Structure Evolution
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ICCV
2007
IEEE
14 years 9 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
CVPR
2005
IEEE
14 years 9 months ago
OBJ CUT
In this paper we present a principled Bayesian method for detecting and segmenting instances of a particular object category within an image, providing a coherent methodology for ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
ECCV
2006
Springer
14 years 9 months ago
Fast Memory-Efficient Generalized Belief Propagation
Generalized Belief Propagation (gbp) has proven to be a promising technique for performing inference on Markov random fields (mrfs). However, its heavy computational cost and large...
M. Pawan Kumar, Philip H. S. Torr
JMLR
2010
169views more  JMLR 2010»
13 years 2 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
CVPR
2007
IEEE
14 years 9 months ago
Mapping Natural Image Patches by Explicit and Implicit Manifolds
Image patches are fundamental elements for object modeling and recognition. However, there has not been a panoramic study of the structures of the whole ensemble of natural image ...
Kent Shi, Song Chun Zhu