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NIPS
2003
14 years 11 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
CVPR
2009
IEEE
16 years 5 months ago
Higher-Order Clique Reduction in Binary Graph Cut
We introduce a new technique that can reduce any higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, w...
Hiroshi Ishikawa 0002
ICCV
2009
IEEE
1655views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Shift-Map Image Editing
Geometric rearrangement of images includes operations such as image retargeting, inpainting, or object rearrangement. Each such operation can be characterized by a shiftmap: the...
Yael Pritch, Eitam Kav-Venaki, Shmuel Peleg
DICTA
2007
14 years 11 months ago
The Tower of Knowledge Scheme for Learning in Computer Vision
A scheme, named tower of knowledge (ToK), is proposed for interpreting 3D scenes. The ToK encapsulates causal dependencies between object appearance and functionality. We demonstr...
Maria Petrou, Mai Xu
ICML
2005
IEEE
15 years 10 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore