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» Learning bilinear models for two-factor problems in vision
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ICCV
2009
IEEE
13 years 8 months ago
Learning to predict where humans look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable ...
Tilke Judd, Krista A. Ehinger, Frédo Durand...
CVBIA
2005
Springer
14 years 3 months ago
A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints
In this paper we present a new framework for image segmentation using probabilistic multinets. We apply this framework to integration of regionbased and contour-based segmentation ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
CVPR
2007
IEEE
15 years 6 days ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
CVPR
2006
IEEE
15 years 6 days ago
Correlated Label Propagation with Application to Multi-label Learning
Many computer vision applications, such as scene analysis and medical image interpretation, are ill-suited for traditional classification where each image can only be associated w...
Feng Kang, Rong Jin, Rahul Sukthankar
BMVC
2010
13 years 5 months ago
Saliency Segmentation based on Learning and Graph Cut Refinement
Saliency detection is a well researched problem in computer vision. In previous work, most of the effort is spent on manually devising a saliency measure. Instead we propose a sim...
Paria Mehrani, Olga Veksler