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NIPS
1997
15 years 7 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
IUI
2012
ACM
14 years 1 months ago
PhysicsBook: a sketch-based interface for animating physics diagrams
We present PhysicsBook, a prototype system that enables users to solve physics problems using a sketch-based interface and then animates any diagram used in solving the problem to...
Salman Cheema, Joseph J. LaViola Jr.
ICCV
2009
IEEE
16 years 11 months ago
Deformable Model Fitting with a Mixture of Local Experts
Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model’s landmarks are found t...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
CVPR
2003
IEEE
16 years 8 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
16 years 8 months ago
Robust Real-Time Visual SLAM Using Scale Prediction and Exemplar Based Feature Description
Two major limitations of real-time visual SLAM algorithms are the restricted range of views over which they can operate and their lack of robustness when faced with erratic camera...
Denis Chekhlov, Mark Pupilli, Walterio W. Mayol-Cu...