Titlebook: Computer Vision – ECCV 2012; 12th European Confer Andrew Fitzgibbon,Svetlana Lazebnik,Cordelia Schmi Conference proceedings 2012 Springer-V

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书目名称Computer Vision – ECCV 2012影响因子(影响力)




书目名称Computer Vision – ECCV 2012影响因子(影响力)学科排名




书目名称Computer Vision – ECCV 2012网络公开度




书目名称Computer Vision – ECCV 2012网络公开度学科排名




书目名称Computer Vision – ECCV 2012被引频次




书目名称Computer Vision – ECCV 2012被引频次学科排名




书目名称Computer Vision – ECCV 2012年度引用




书目名称Computer Vision – ECCV 2012年度引用学科排名




书目名称Computer Vision – ECCV 2012读者反馈




书目名称Computer Vision – ECCV 2012读者反馈学科排名

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Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spacesow that we are able to speed up inference in these models around 10-30 times with respect to competing graph-cut/move-making methods, as well as maintaining or improving accuracy in all cases. We show results on PascalVOC-10 for object class segmentation, and Leuven for joint object-stereo labeling.

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CHASM

A Locally Linear Regression Model for Boundary Preserving Regularization in Stereo Matchingserving boundary sharpness while keeping regions smooth. We also evaluate our method on a wide range of challenging real-world videos. Experimental results show that our method outperforms existing methods in temporal consistency.

STAT

Annotate

Annotate

刀锋

MONY

Vassilis K. Fouskas,Bülent Gökayproximate solutions even for submodular functions. We show experimentally that our implementation of the Generic Cuts algorithm is more than an order of magnitude faster than all algorithms including reduction based whose outputs on submodular potentials are near optimal.

Omnipotent