43 search results - page 1 / 9 » A Bayesian Approach to Unsupervised One-Shot Learning of Obj... |
ICCV
2003
IEEE
14 years 6 months ago
2003
IEEE
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...
CVPR
2010
IEEE
14 years 1 months ago
2010
IEEE
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
DAGM
2006
Springer
13 years 8 months ago
2006
Springer
Recently, many approaches have been proposed for visual object category detection. They vary greatly in terms of how much supervision is needed. High performance object detection m...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...