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TKDE
2012
245views Formal Methods» more  TKDE 2012»
13 years 1 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 3 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 2 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu
CVPR
2007
IEEE
16 years 19 days ago
Fast Human Pose Estimation using Appearance and Motion via Multi-Dimensional Boosting Regression
We address the problem of estimating human pose in video sequences, where rough location has been determined. We exploit both appearance and motion information by defining suitabl...
Alessandro Bissacco, Ming-Hsuan Yang, Stefano Soat...
ECCV
2004
Springer
16 years 15 days ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona