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» Structured Learning and Prediction in Computer Vision
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CVPR
2007
IEEE
14 years 10 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
ECCV
2006
Springer
14 years 10 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
CGF
2007
135views more  CGF 2007»
13 years 8 months ago
Prediction of Individual Non-Linear Aging Trajectories of Faces
Represented in a Morphable Model, 3D faces follow curved trajectories in face space as they age. We present a novel algorithm that computes the individual aging trajectories for g...
Kristina Scherbaum, Martin Sunkel, Hans-Peter Seid...
CVPR
2004
IEEE
14 years 10 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
ICPR
2008
IEEE
14 years 9 months ago
Supervised learning of a generative model for edge-weighted graphs
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...
Andrea Torsello, David L. Dowe