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» Learning bilinear models for two-factor problems in vision
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ECCV
2008
Springer
13 years 9 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
CVPR
2006
IEEE
14 years 1 months ago
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the import...
Leonid Sigal, Michael J. Black
CVPR
2009
IEEE
15 years 2 months ago
Coupled Spectral Regression for Matching Heterogeneous Faces
Face recognition algorithms need to deal with variable lighting conditions. Near infrared (NIR) image based face recognition technology has been proposed to effectively overcome...
Stan Z. Li, Zhen Lei
ICCV
1998
IEEE
13 years 12 months ago
Condensing Image Databases when Retrieval is Based on Non-Metric Distances
One of the key problems in appearance-based vision is understanding how to use a set of labeled images to classify new images. Classification systems that can model human performa...
David W. Jacobs, Daphna Weinshall, Yoram Gdalyahu
CVPR
2012
IEEE
11 years 10 months ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...