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ECCV
2010
Springer
13 years 4 months ago
Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision
The saddle point framework provides a convenient way to formulate many convex variational problems that occur in computer vision. The framework unifies a broad range of data and re...
Jan Lellmann, Dirk Breitenreicher, Christoph Schn&...
CVPR
2009
IEEE
14 years 10 months ago
A Convex Relaxation Approach for Computing Minimal Partitions
In this work we propose a convex relaxation approach for computing minimal partitions. Our approach is based on rewriting the minimal partition problem (also known as Potts mode...
Thomas Pock (Graz University of Technology), Anton...
ECCV
2008
Springer
14 years 5 months ago
Non-local Regularization of Inverse Problems
This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This nonlocal graph allows to adapt the penalization to t...
Gabriel Peyré, Laurent D. Cohen, Séb...
CVPR
2008
IEEE
14 years 5 months ago
An efficient algorithm for compressed MR imaging using total variation and wavelets
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
ICPR
2010
IEEE
13 years 5 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With