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ICCV
2011
IEEE
14 years 6 months ago
Manhattan Scene Understanding Using Monocular, Stereo, and 3D Features
This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through struct...
Alex Flint, David Murray, Ian Reid
CVPR
2012
IEEE
13 years 9 months ago
Unsupervised co-segmentation through region matching
Co-segmentation is defined as jointly partitioning multiple images depicting the same or similar object, into foreground and background. Our method consists of a multiplescale mu...
José C. Rubio, Joan Serrat, Antonio M. L&oa...
CVPR
2012
IEEE
13 years 9 months ago
Meta-class features for large-scale object categorization on a budget
In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...
Alessandro Bergamo, Lorenzo Torresani
CVPR
2009
IEEE
1096views Computer Vision» more  CVPR 2009»
17 years 1 months ago
How far can you get with a modern face recognition test set using only simple features?
In recent years, large databases of natural images have become increasingly popular in the evaluation of face and object recognition algorithms. However, Pinto et al. previously ...
Nicolas Pinto, James J. DiCarlo, David D. Cox
SIGGRAPH
1997
ACM
15 years 10 months ago
Recovering high dynamic range radiance maps from photographs
We present a method of recovering high dynamic range radiance maps from photographs taken with conventional imaging equipment. In our method, multiple photographs of the scene are...
Paul E. Debevec, Jitendra Malik