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CVPR
2003
IEEE
14 years 11 months ago
Nonparametric Belief Propagation
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
CVPR
2007
IEEE
14 years 11 months ago
Semi-supervised Hierarchical Models for 3D Human Pose Reconstruction
Recent research in visual inference from monocular images has shown that discriminatively trained image-based predictors can provide fast, automatic qualitative 3D reconstructions...
Atul Kanaujia, Cristian Sminchisescu, Dimitris N. ...
ICCV
2007
IEEE
14 years 4 months ago
Scale-Dependent 3D Geometric Features
Three-dimensional geometric data play fundamental roles in many computer vision applications. However, their scale-dependent nature, i.e. the relative variation in the spatial ext...
John Novatnack, Ko Nishino
CVPR
2003
IEEE
14 years 11 months ago
PAMPAS: Real-Valued Graphical Models for Computer Vision
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Michael Isard
JMLR
2010
141views more  JMLR 2010»
13 years 4 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi