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CVPR
2007
IEEE
15 years 11 months ago
Semantic Hierarchies for Visual Object Recognition
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...
Marcin Marszalek, Cordelia Schmid
IJCV
2007
196views more  IJCV 2007»
14 years 9 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman
79
Voted
ADMA
2006
Springer
167views Data Mining» more  ADMA 2006»
15 years 3 months ago
A Correlation Approach for Automatic Image Annotation
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
David R. Hardoon, Craig Saunders, Sándor Sz...
ICRA
2009
IEEE
173views Robotics» more  ICRA 2009»
15 years 4 months ago
Most salient region tracking
— In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to...
Simone Frintrop, Markus Kessel
ICCV
2003
IEEE
15 years 11 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona