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» Variations on U-Shaped Learning
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101
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ICCV
1999
IEEE
15 years 5 months ago
Learning Low-Level Vision
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...
William T. Freeman, Egon C. Pasztor
PVLDB
2008
117views more  PVLDB 2008»
15 years 9 days ago
Learning to extract form labels
In this paper we describe a new approach to extract element labels from Web form interfaces. Having these labels is a requirement for several techniques that attempt to retrieve a...
Hoa Nguyen, Thanh Hoang Nguyen, Juliana Freire
106
Voted
BMVC
2010
14 years 11 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
132
Voted
CVPR
2011
IEEE
14 years 4 months ago
Learning People Detection Models from Few Training Samples
People detection is an important task for a wide range of applications in computer vision. State-of-the-art methods learn appearance based models requiring tedious collection and ...
Leonid Pishchulin, Christian Wojek, Arjun Jain, Th...
108
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Maximum marginal likelihood estimation for nonnegative dictionary learning
We describe an alternative to standard nonnegative matrix factorisation (NMF) for nonnegative dictionary learning. NMF with the Kullback-Leibler divergence can be seen as maximisa...
Onur Dikmen, Cédric Févotte