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» Learning bilinear models for two-factor problems in vision
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CVPR
2008
IEEE
15 years 6 days ago
3D occlusion recovery using few cameras
We present a practical framework for detecting and modeling 3D static occlusions for wide-baseline, multi-camera scenarios where the number of cameras is small. The framework cons...
Mark A. Keck, James W. Davis
CVPR
2009
IEEE
1848views Computer Vision» more  CVPR 2009»
15 years 4 months ago
Moving Cast Shadow Detection using Physics-based Features
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...
Jia-Bin Huang and Chu-Song Chen
ICCV
2011
IEEE
12 years 10 months ago
Incremental On-line Semi-supervised Learning for Segmenting the Left Ventricle of the Heart from Ultrasound Data
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
Gustavo Carneiro, Jacinto C. Nascimento
ICCV
2009
IEEE
15 years 3 months ago
Unlabeled data improves word prediction
Labeling image collections is a tedious task, especially when multiple labels have to be chosen for each image. In this paper we introduce a new framework that extends state of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
ICCV
2011
IEEE
12 years 10 months ago
Learning Cross-modality Similarity for Multinomial Data
Many applications involve multiple-modalities such as text and images that describe the problem of interest. In order to leverage the information present in all the modalities, on...
Yangqing Jia, Mathieu Salzmann, Trevor Darrell