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» Learning Generic Prior Models for Visual Computation
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CVPR
2008
IEEE
15 years 11 months ago
Local deformation models for monocular 3D shape recovery
Without a deformation model, monocular 3D shape recovery of deformable surfaces is severly under-constrained. Even when the image information is rich enough, prior knowledge of th...
Mathieu Salzmann, Raquel Urtasun, Pascal Fua
CVPR
2011
IEEE
14 years 5 months ago
Random Field Topic Model for Semantic Region Analysis in Crowded Scenes from Tracklets
In this paper, a Random Field Topic (RFT) model is proposed for semantic region analysis from motions of objects in crowded scenes. Different from existing approaches of learning ...
Bolei Zhou, Xiaogang Wang
ACL
2010
14 years 7 months ago
Phylogenetic Grammar Induction
We present an approach to multilingual grammar induction that exploits a phylogeny-structured model of parameter drift. Our method does not require any translated texts or token-l...
Taylor Berg-Kirkpatrick, Dan Klein
NIPS
2007
14 years 11 months ago
On Sparsity and Overcompleteness in Image Models
Computational models of visual cortex, and in particular those based on sparse coding, have enjoyed much recent attention. Despite this currency, the question of how sparse or how...
Pietro Berkes, Richard Turner, Maneesh Sahani
HUMO
2007
Springer
15 years 3 months ago
Modeling Human Locomotion with Topologically Constrained Latent Variable Models
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
Raquel Urtasun, David J. Fleet, Neil D. Lawrence