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CVPR
2009
IEEE
1382views Computer Vision» more  CVPR 2009»
15 years 2 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
15 years 21 days 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
ECCV
2006
Springer
14 years 9 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
ICIP
2007
IEEE
14 years 9 months ago
A Multi-Layer MRF Model for Object-Motion Detection in Unregistered Airborne Image-Pairs
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse mat...
Csaba Benedek, Tamas Sziranyi, Zoltan Kato, and Jo...
ICIP
2003
IEEE
14 years 9 months ago
A semantic representation for image retrieval
Robust semantic labeling of image regions is a basic problem in representing and retrieving image/video content. We propose an SVM-MRF framework to model features and their spatia...
Lei Wang, B. S. Manjunath