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» A Framework for Multiple-Instance Learning
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ICCV
2007
IEEE
16 years 9 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
ICCV
2005
IEEE
16 years 8 months ago
Geometric Context from a Single Image
Many computer vision algorithms limit their performance by ignoring the underlying 3D geometric structure in the image. We show that we can estimate the coarse geometric propertie...
Derek Hoiem, Alexei A. Efros, Martial Hebert
ICIP
2005
IEEE
16 years 8 months ago
Non-parametric image super-resolution using multiple images
In this paper, we present a novel learning based framework for performing super-resolution using multiple images. We model the image as an undirected graphical model over image pa...
Mithun Das Gupta, ShyamSundar Rajaram, Nemanja Pet...
ICIP
2003
IEEE
16 years 8 months ago
Incorporating complex statistical information in active contour-based image segmentation
We propose an information-theoretic method for multi-phase image segmentation, in an active contour-based framework. Our approach is based on nonparametric density estimates, and ...
Alan S. Willsky, Anthony J. Yezzi, John W. Fisher ...
ICPR
2008
IEEE
16 years 8 months ago
Hand posture recognition with co-training
As an emerging human-computer interaction approachvision based hand interaction is more natural and efficient. Howeverin order to achieve high accuracy, most of the existing hand ...
Yikai Fang, Jian Cheng, Jinqiao Wang, Kongqiao Wan...