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» On learning with dissimilarity functions
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17 years 10 days ago
The Berkeley Segmentation Engine (BSE)
The code is a (good, in my opinion) implementation of a segmentation engine based on normalised cuts (a spectral clustering algorithm) and a pixel affinity matrix calculation algor...
Charless Fowlkes
164
Voted
CVPR
2008
IEEE
16 years 8 months ago
3D occlusion recovery using few cameras
We present a practical framework for detecting and modeling 3D static occlusions for wide-baseline, multi-camera scenarios where the number of cameras is small. The framework cons...
Mark A. Keck, James W. Davis
ICCV
2003
IEEE
16 years 8 months ago
Bayesian Clustering of Optical Flow Fields
We present a method for unsupervised learning of classes of motions in video. We project optical flow fields to a complete, orthogonal, a-priori set of basis functions in a probab...
Jesse Hoey, James J. Little
189
Voted
ECCV
2008
Springer
16 years 8 months ago
SERBoost: Semi-supervised Boosting with Expectation Regularization
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
Amir Saffari, Helmut Grabner, Horst Bischof
ICIP
2006
IEEE
16 years 8 months ago
Sparse Image Reconstruction using Sparse Priors
Sparse image reconstruction is of interest in the fields of radioastronomy and molecular imaging. The observation is assumed to be a linear transformation of the image, and corrup...
Michael Ting, Raviv Raich, Alfred O. Hero