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» Learning to Estimate Scenes from Images
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CVPR
2008
IEEE
14 years 11 months ago
Extracting a fluid dynamic texture and the background from video
Given the video of a still background occluded by a fluid dynamic texture (FDT), this paper addresses the problem of separating the video sequence into its two constituent layers....
Bernard Ghanem, Narendra Ahuja
ICASSP
2010
IEEE
13 years 9 months ago
A minimax approach to Bayesian estimation with partial knowledge of the observation model
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
Tomer Michaeli, Yonina C. Eldar
CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
DAGM
2004
Springer
14 years 2 months ago
Scale-Invariant Object Categorization Using a Scale-Adaptive Mean-Shift Search
The goal of our work is object categorization in real-world scenes. That is, given a novel image we want to recognize and localize unseen-before objects based on their similarity t...
Bastian Leibe, Bernt Schiele
ICIP
2006
IEEE
14 years 11 months ago
Prioritized Sequential 3D Reconstruction in Video Sequences with Multiple Motions
In this study, an algorithm is proposed to solve the multi-frame structure from motion (MFSfM) problem for monocular video sequences in dynamic scenes. The algorithm uses the epip...
Evren Imre, Sebastian Knorr, A. Aydin Alatan, Thom...