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» Unsupervised Learning of Object Deformation Models
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ICCV
2001
IEEE
14 years 9 months ago
Separating Appearance from Deformation
By representing images and image prototypes by linear subspaces spanned by "tangent vectors" (derivatives of an image with respect to translation, rotation, etc.), impre...
Nebojsa Jojic, Patrice Simard, Brendan J. Frey, Da...
NIPS
2008
13 years 8 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
CVPR
2012
IEEE
11 years 9 months ago
From Pictorial Structures to deformable structures
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connecte...
Silvia Zuffi, Oren Freifeld, Michael J. Black
PAMI
2008
170views more  PAMI 2008»
13 years 7 months ago
Unsupervised Category Modeling, Recognition, and Segmentation in Images
Suppose a set of arbitrary (unlabeled) images contains frequent occurrences of 2D objects from an unknown category. This paper is aimed at simultaneously solving the following rel...
Sinisa Todorovic, Narendra Ahuja
ICCV
1998
IEEE
14 years 9 months ago
Sectored Snakes: Evaluating Learned-Energy Segmentations
We describe how to teach deformable models to maximize image segmentation correctness based on user-specified criteria, and we present a method for evaluating which criteria work ...
Samuel D. Fenster, John R. Kender