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» A Conditional Random Field Model for Video Super-resolution
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ICASSP
2009
IEEE
14 years 9 months ago
Applying discretized articulatory knowledge to dysarthric speech
This paper applies two dynamic Bayes networks that include theoretical and measured kinematic features of the vocal tract, respectively, to the task of labeling phoneme sequences ...
Frank Rudzicz
ICASSP
2010
IEEE
14 years 12 months ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
CVPR
2012
IEEE
13 years 2 months ago
Joint 2D-3D temporally consistent semantic segmentation of street scenes
In this paper we propose a novel Conditional Random Field (CRF) formulation for the semantic scene labeling problem which is able to enforce temporal consistency between consecuti...
Georgios Floros, Bastian Leibe
DCC
2005
IEEE
15 years 11 months ago
When is Bit Allocation for Predictive Video Coding Easy?
This paper addresses the problem of bit allocation among frames in a predictively encoded video sequence. Finding optimal solutions to this problem potentially requires making an ...
Yegnaswamy Sermadevi, Jun Chen, Sheila S. Hemami, ...
CVPR
2012
IEEE
13 years 2 months ago
Top-down and bottom-up cues for scene text recognition
Scene text recognition has gained significant attention from the computer vision community in recent years. Recognizing such text is a challenging problem, even more so than the ...
Anand Mishra, Karteek Alahari, C. V. Jawahar