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» Adaptative Markov Random Fields for Omnidirectional Vision
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ICDAR
2007
IEEE
14 years 1 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
ECCV
2008
Springer
14 years 9 months ago
Analysis of Building Textures for Reconstructing Partially Occluded Facades
Abstract. As part of an architectural modeling project, this paper investigates the problem of understanding and manipulating images of buildings. Our primary motivation is to auto...
Thommen Korah, Christopher Rasmussen
ECCV
2004
Springer
14 years 9 months ago
MCMC-Based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points
We investigate the automated reconstruction of piecewise smooth 3D curves, using subdivision curves as a simple but flexible curve representation. This representation allows taggin...
Michael Kaess, Rafal Zboinski, Frank Dellaert
ICIP
2006
IEEE
14 years 9 months ago
Spatially Constrained Wiener Filter with Markov Autocorrelation Modeling for Image Resolution Enhancement
This paper develops a practical method for image resolution enhancement. The method optimizes the spatially constrained Wiener filter for an efficiently parameterized model of the...
Jiazheng Shi, Stephen E. Reichenbach
DAGM
2008
Springer
13 years 9 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr