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» Matching Algorithms Are Fast in Sparse Random Graphs
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CVPR
2009
IEEE
15 years 4 months ago
Efficient Planar Graph Cuts with Applications in Computer Vision
We present a fast graph cut algorithm for planar graphs. It is based on the graph theoretical work [2] and leads to an efficient method that we apply on shape matching and im- a...
Daniel Cremers, Eno Töppe, Frank R. Schmidt
ASAP
2008
IEEE
105views Hardware» more  ASAP 2008»
13 years 11 months ago
Fast custom instruction identification by convex subgraph enumeration
Automatic generation of custom instruction processors from high-level application descriptions enables fast design space exploration, while offering very favorable performance and...
Kubilay Atasu, Oskar Mencer, Wayne Luk, Can C. &Ou...
IPPS
2005
IEEE
14 years 2 months ago
MaTCH : Mapping Data-Parallel Tasks on a Heterogeneous Computing Platform Using the Cross-Entropy Heuristic
We propose in this paper a heuristic for mapping a set of interacting tasks of a parallel application onto a heterogeneous computing platform such as a computational grid. Our nov...
Soumya Sanyal, Sajal K. Das
MM
2010
ACM
238views Multimedia» more  MM 2010»
13 years 9 months ago
Vlfeat: an open and portable library of computer vision algorithms
VLFeat is an open and portable library of computer vision algorithms. It aims at facilitating fast prototyping and reproducible research for computer vision scientists and student...
Andrea Vedaldi, Brian Fulkerson
PAMI
2007
176views more  PAMI 2007»
13 years 8 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas