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JCDL
2004
ACM
127views Education» more  JCDL 2004»
15 years 7 months ago
Collection understanding
Collection understanding shifts the traditional focus of retrieval in large collections from locating specific artifacts to gaining a comprehensive view of the collection. Visuali...
Michelle Chang, John J. Leggett, Richard Furuta, A...
CVPR
2008
IEEE
15 years 8 months ago
Scene understanding with discriminative structured prediction
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Jinhui Yuan, Jianmin Li, Bo Zhang
CGF
2004
93views more  CGF 2004»
15 years 1 months ago
Instant Volumetric Understanding with Order-Independent Volume Rendering
Rapid, visual understanding of volumetric datasets is a crucial outcome of a good volume rendering application, but few current volume rendering systems deliver this result. Our g...
Benjamin Mora, David S. Ebert
CVPR
2009
IEEE
1866views Computer Vision» more  CVPR 2009»
16 years 9 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...
108
Voted
CVPR
2003
IEEE
16 years 3 months ago
Probabilistic Spatial Context Models for Scene Content Understanding
Scene content understanding facilitates a large number of applications, ranging from content-based image retrieval to other multimedia applications. Material detection refers to t...
Amit Singhal, Jiebo Luo, Weiyu Zhu