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CVPR
2009
IEEE
1382views Computer Vision» more  CVPR 2009»
15 years 5 months ago
Super-Resolution via Recapture and Bayesian Effect Modeling
This paper presents Bayesian edge inference (BEI), a single-frame super-resolution method explicitly grounded in Bayesian inference that addresses issues common to existing meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
ICCV
2009
IEEE
2301views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Class Segmentation and Object Localization with Superpixel Neighborhoods
We propose a method to identify and localize object classes in images. Instead of operating at the pixel level, we advocate the use of superpixels as the basic unit of a class s...
Brian Fulkerson, Andrea Vedaldi, Stefano Soatto
ICCV
2009
IEEE
15 years 3 months ago
Higher-Order Gradient Descent by Fusion-Move Graph Cut
Markov Random Field is now ubiquitous in many formulations of various vision problems. Recently, optimization of higher-order potentials became practical using higherorder graph...
Hiroshi Ishikawa
ICCV
2007
IEEE
15 years 1 days ago
Objects in Context
In the task of visual object categorization, semantic context can play the very important role of reducing ambiguity in objects' visual appearance. In this work we propose to...
Andrew Rabinovich, Andrea Vedaldi, Carolina Galleg...
ECCV
2006
Springer
14 years 12 months ago
Smooth Image Segmentation by Nonparametric Bayesian Inference
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
Peter Orbanz, Joachim M. Buhmann