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» PAMPAS: Real-Valued Graphical Models for Computer Vision
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CVPR
2005
IEEE
14 years 6 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
FTCGV
2011
122views more  FTCGV 2011»
12 years 8 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
SIGGRAPH
1998
ACM
13 years 9 months ago
A Multiscale Model of Adaptation and Spatial Vision for Realistic Image Display
In this paper we develop a computational model of adaptation and spatial vision for realistic tone reproduction. The model is based on a multiscale representation of pattern, lumi...
Sumanta N. Pattanaik, James A. Ferwerda, Mark D. F...
ICCV
2011
IEEE
12 years 4 months ago
Learning to Cluster Using High Order Graphical Models with Latent Variables
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
Nikos Komodakis