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» Global Ranking Using Continuous Conditional Random Fields
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ECCV
2006
Springer
14 years 9 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
SIGIR
2009
ACM
14 years 2 months ago
Global ranking by exploiting user clicks
It is now widely recognized that user interactions with search results can provide substantial relevance information on the documents displayed in the search results. In this pape...
Shihao Ji, Ke Zhou, Ciya Liao, Zhaohui Zheng, Gui-...
CVPR
2009
IEEE
15 years 2 months ago
Continuous Maximal Flows and Wulff Shapes: Application to MRFs
Convex and continuous energy formulations for low level vision problems enable efficient search procedures for the corresponding globally optimal solutions. In this work we exte...
Christopher Zach (UNC Chapel Hill), Marc Niethamme...
PAMI
2010
215views more  PAMI 2010»
13 years 6 months ago
Fusion Moves for Markov Random Field Optimization
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...
ICCV
2005
IEEE
14 years 9 months ago
Globally Optimal Solutions for Energy Minimization in Stereo Vision Using Reweighted Belief Propagation
A wide range of low level vision problems have been formulated in terms of finding the most probable assignment of a Markov Random Field (or equivalently the lowest energy configu...
Talya Meltzer, Chen Yanover, Yair Weiss