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» Learning to localize detected objects
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147
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ICCV
2003
IEEE
16 years 6 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
ACCV
1998
Springer
15 years 8 months ago
Appearance Based Visual Learning and Object Recognition with Illumination Invariance
This paper describes a method for recognizing partially occluded objects under different levels of illumination brightness by using the eigenspace analysis. In our previous work, w...
Kohtaro Ohba, Yoichi Sato, Katsushi Ikeuchi
ICCV
2009
IEEE
16 years 9 months ago
Joint learning of visual attributes, object classes and visual saliency
We present a method to learn visual attributes (eg.“red”, “metal”, “spotted”) and object classes (eg. “car”, “dress”, “umbrella”) together. We assume imag...
Gang Wang, David Forsyth
BMCV
2000
Springer
15 years 9 months ago
Towards a Computational Model for Object Recognition in IT Cortex
First IEEE International Workshop on Biologically Motivated Computer Vision, Seoul, Korea (May 2000). There is considerable evidence that object recognition in primates is based o...
David G. Lowe
160
Voted
CVPR
2005
IEEE
16 years 6 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman