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AAAI
2011
14 years 3 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
157
Voted
CVPR
2012
IEEE
13 years 6 months ago
Learning 3D object templates by hierarchical quantization of geometry and appearance spaces
This paper presents a method for learning 3D object templates from view labeled object images. The 3D template is defined in a joint appearance and geometry space, and is compose...
Wenze Hu
142
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INTERACTIONS
2010
97views more  INTERACTIONS 2010»
15 years 1 months ago
Design challenge based learning (DCBL) and sustainable pedagogical practice
s on Human Factors in Computing Systems. CHI ‘07. New York: ACM, 2007. university environment at scale, with structure, and with rigor. The notion of studio culture and learning ...
Eli Blevis
PR
2007
96views more  PR 2007»
15 years 3 months ago
Weighted and robust learning of subspace representations
A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions....
Danijel Skocaj, Ales Leonardis, Horst Bischof
196
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ICASSP
2010
IEEE
15 years 2 months ago
Human detection in images via L1-norm Minimization Learning
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Ran Xu, Baochang Zhang, Qixiang Ye, Jianbin Jiao