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CVPR
2009
IEEE
1866views Computer Vision» more  CVPR 2009»
16 years 5 months ago
Understanding and evaluating blind deconvolution algorithms
Blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of...
Anat Levin, Yair Weiss, Frédo Durand, Willi...
114
Voted
CVPR
2009
IEEE
16 years 5 months ago
Boosted Multi-Task Learning for Face Verification With Applications to Web Image and Video Search
Face verification has many potential applications including filtering and ranking image/video search results on celebrities. Since these images/videos are taken under uncontrolle...
Xiaogang Wang (MIT), Cha Zhang (Microsoft Research...
133
Voted
CVPR
2009
IEEE
16 years 5 months ago
Illumination and Spatially Varying Specular Reflectance from a Single View
Estimating the illumination and the reflectance properties of an object surface from a sparse set of images is an important but inherently ill-posed problem. The problem becomes...
Kenji Hara (Kyushu University), Ko Nishino (Drexel...
CVPR
2009
IEEE
16 years 5 months ago
Learning Shape Prior Models for Object Matching
The aim of this work is to learn a shape prior model for an object class and to improve shape matching with the learned shape prior. Given images of example instances, we can le...
Cordelia Schmid, Frédéric Jurie, Tin...
85
Voted
CVPR
2009
IEEE
1084views Computer Vision» more  CVPR 2009»
16 years 5 months ago
Describing Objects by their Attributes
We propose to shift the goal of recognition from naming to describing. Doing so allows us not only to name familiar objects, but also: to report unusual aspects of a familiar ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...