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» Robust Learning - Rich and Poor
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ECCV
2008
Springer
16 years 6 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
ECCV
2008
Springer
16 years 6 months ago
Automatic Image Colorization Via Multimodal Predictions
We aim to color greyscale images automatically, without any manual intervention. The color proposition could then be interactively corrected by user-provided color landmarks if nec...
Bernhard Schölkopf, Guillaume Charpiat, Matth...
ECCV
2004
Springer
16 years 6 months ago
A Visual Category Filter for Google Images
We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The parts and their spatial co...
Robert Fergus, Pietro Perona, Andrew Zisserman
ECCV
2006
Springer
16 years 6 months ago
Dense Photometric Stereo by Expectation Maximization
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...
Tai-Pang Wu, Chi-Keung Tang
ECCV
2006
Springer
16 years 6 months ago
Feature Harvesting for Tracking-by-Detection
We propose a fast approach to 3?D object detection and pose estimation that owes its robustness to a training phase during which the target object slowly moves with respect to the ...
Mustafa Özuysal, Vincent Lepetit, Franç...