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» Multiscale Conditional Random Fields for Image Labeling
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ECCV
2010
Springer
14 years 2 months ago
Graph Cut based Inference with Co-occurrence Statistics
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
TIP
2010
129views more  TIP 2010»
13 years 3 months ago
Image Segmentation by MAP-ML Estimations
Abstract--Image segmentation plays an important role in computer vision and image analysis. In this paper, image segmentation is formulated as a labeling problem under a probabilit...
Shifeng Chen, Liangliang Cao, Yueming Wang, Jianzh...
ACL
2009
13 years 6 months ago
Do Automatic Annotation Techniques Have Any Impact on Supervised Complex Question Answering?
In this paper, we analyze the impact of different automatic annotation methods on the performance of supervised approaches to the complex question answering problem (defined in th...
Yllias Chali, Sadid A. Hasan, Shafiq R. Joty
CVPR
2007
IEEE
14 years 10 months ago
Iterative MAP and ML Estimations for Image Segmentation
Image segmentation plays an important role in computer vision and image analysis. In this paper, the segmentation problem is formulated as a labeling problem under a probability m...
Shifeng Chen, Liangliang Cao, Jianzhuang Liu, Xiao...
CVPR
2009
IEEE
15 years 3 months ago
An Empirical Bayes Approach to Contextual Region Classification
This paper presents a nonparametric approach to labeling of local image regions that is inspired by recent developments in information-theoretic denoising. The chief novelty of ...
Svetlana Lazebnik (UNC Chapel Hill), Maxim Raginsk...