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» Learning the parts of objects by auto-association
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ECCV
2000
Springer
14 years 9 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
CVPR
2005
IEEE
14 years 9 months ago
Identifying Semantically Equivalent Object Fragments
We describe a novel technique for identifying semantically equivalent parts in images belonging to the same object class, (e.g. eyes, license plates, aircraft wings etc.). The vis...
Boris Epshtein, Shimon Ullman
ECCV
2010
Springer
14 years 23 days ago
Weakly Supervised Shape Based Object Detection with Particle Filter
Abstract. We describe an efficient approach to construct shape models composed of contour parts with partially-supervised learning. The proposed approach can easily transfer parts ...
PAMI
2008
250views more  PAMI 2008»
13 years 7 months ago
Combined Top-Down/Bottom-Up Segmentation
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Eran Borenstein, Shimon Ullman
CVPR
2007
IEEE
14 years 9 months ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher