CVPR
2012
IEEE
12 years 5 months ago
2012
IEEE
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
111
click to vote
DAGM
2011
Springer
13 years 2 months ago
2011
Springer
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
ECML
2007
Springer
14 years 9 months ago
2007
Springer
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
CVPR
2010
IEEE
14 years 11 months ago
2010
IEEE
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...