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CORR
2011
Springer
222views Education» more  CORR 2011»
12 years 8 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
CVPR
2010
IEEE
1135views Computer Vision» more  CVPR 2010»
14 years 23 days ago
Towards Weakly Supervised Semantic Segmentation by Means of Multiple Instance and Multitask Learning.
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...
Alexander Vezhnevets, Joachim Buhmann
CVPR
2012
IEEE
11 years 7 months ago
Weakly supervised structured output learning for semantic segmentation
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...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
ECCV
2006
Springer
14 years 6 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
CVPR
2011
IEEE
13 years 1 months ago
Boundary Preserving Dense Local Regions
We propose a dense local region detector to extract features suitable for image matching and object recognition tasks. Whereas traditional local interest operators rely on repeata...
Jaechul Kim, Kristen Grauman