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» Decomposition of range images using markov random fields
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CVPR
2005
IEEE
14 years 10 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
DAS
2008
Springer
13 years 10 months ago
Super-Resolution of Text Images Using Edge-Directed Tangent Field
This paper presents an edge-directed super-resolution algorithm for gray level document images without using any training set. This technique creates an image with smooth regions ...
Jyotirmoy Banerjee, C. V. Jawahar
CVPR
2007
IEEE
14 years 10 months ago
Efficient Belief Propagation for Vision Using Linear Constraint Nodes
Belief propagation over pairwise connected Markov Random Fields has become a widely used approach, and has been successfully applied to several important computer vision problems....
Brian Potetz
ICCV
2001
IEEE
14 years 10 months ago
Markov Face Models
The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face ...
Sarat C. Dass, Anil K. Jain
CVPR
2007
IEEE
14 years 10 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs