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» A Conditional Random Field Model for Video Super-resolution
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AVSS
2008
IEEE
13 years 7 months ago
Super-Resolution of Facial Images in Video with Expression Changes
Super-resolution (SR) of facial images from video suffers from facial expression changes. Most of the existing SR algorithms for facial images make an unrealistic assumption that ...
Jiangang Yu, Bir Bhanu
CVPR
2009
IEEE
1382views Computer Vision» more  CVPR 2009»
15 years 1 days 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 ...
ICPR
2006
IEEE
13 years 11 months ago
A Conditional Random Field Model for Video Super-resolution
In this paper, we propose a learning-based method for video super-resolution. There are two main contributions of the proposed method. First, information from cameras with differe...
Dan Kong, Mei Han, Wei Xu, Hai Tao, Yihong Gong
CVPR
2005
IEEE
14 years 7 months ago
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Qiang Ji, Yang Wang 0002
CVPR
2011
IEEE
13 years 1 months ago
Identifying Players in Broadcast Sports Videos using Conditional Random Fields
We are interested in the problem of automatic tracking and identification of players in broadcast sport videos shot with a moving camera from a medium distance. While there are m...
Wei-Lwun Lu, Jo-Anne Ting, Kevin Murphy, Jim Littl...