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» Statistical Models of Appearance for Computer Vision
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CVPR
2005
IEEE
16 years 5 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
121
Voted
ECCV
2010
Springer
15 years 8 months ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
158
Voted
ICCV
2011
IEEE
14 years 3 months ago
Video Primal Sketch: A Generic Middle-Level Representation of Video
This paper presents a middle-level video representation named Video Primal Sketch (VPS), which integrates two regimes of models: i) sparse coding model using static or moving prim...
Zhi Han, Zongben Xu, Song-Chun Zhu
163
Voted
MM
2005
ACM
250views Multimedia» more  MM 2005»
15 years 9 months ago
An object-based video coding framework for video sequences obtained from static cameras
This paper presents a novel object-based video coding framework for videos obtained from a static camera. As opposed to most existing methods, the proposed method does not require...
Asaad Hakeem, Khurram Shafique, Mubarak Shah
CVPR
2009
IEEE
3248views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Single Image Haze Removal Using Dark Channel Prior
In this paper, we propose a simple but effective image prior - dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of the...
Kaiming He (The Chinese University of Hong Kong), ...