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IJCV
2008
266views more  IJCV 2008»
15 years 4 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 2 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...
ACCV
2010
Springer
14 years 11 months ago
An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
Chavdar Papazov, Darius Burschka
CVPR
2009
IEEE
3248views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Single Image Haze Removal Using Dark Channel Prior
In this paper, we propose a simple but effective image prior - dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of the...
Kaiming He (The Chinese University of Hong Kong), ...
CVPR
2009
IEEE
16 years 11 months ago
Continuous Ratio Optimization via Convex Relaxation with Applications to Multiview 3D Reconstruction
We introduce a convex relaxation framework to optimally minimize continuous surface ratios. The key idea is to minimize the continuous surface ratio by solving a sequence of con...
Kalin Kolev (University of Bonn), Daniel Cremers (...