Graph cuts in computer vision

Known as: Graph cut, Graph cut segmentation 
As applied in the field of computer vision, graph cuts can be employed to efficiently solve a wide variety of low-level computer vision problems… (More)
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Topic mentions per year

Topic mentions per year

1991-2017
05010019912017

Papers overview

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Highly Cited
2010
Highly Cited
2010
Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as… (More)
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2009
2009
We present a fast graph cut algorithm for planar graphs. It is based on the graph theoretical work and leads to an efficient… (More)
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Highly Cited
2007
Highly Cited
2007
In this paper, we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. We show how this algorithm can… (More)
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Highly Cited
2006
Highly Cited
2006
Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper… (More)
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Highly Cited
2005
Highly Cited
2005
The recent explosion of interest in graph cut methods in computer vision naturally spawns the question: what energy functions can… (More)
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Highly Cited
2005
Highly Cited
2005
Phase unwrapping is the inference of absolute phase from modulo-2pi phase. This paper introduces a new energy minimization… (More)
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Highly Cited
2005
Highly Cited
2005
In this paper, we present a fast new fully dynamic algorithm for the st-mincut/max-flow problem. We show how this algorithm can… (More)
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Highly Cited
2005
Highly Cited
2005
Interactive or semi-automatic segmentation is a useful alternative to pure automatic segmentation in many applications. While… (More)
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Highly Cited
2003
Highly Cited
2003
Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method… (More)
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Highly Cited
2003
Highly Cited
2003
In this paper we introduce a new algorithm for image and video texture synthesis. In our approach, patch regions from a sample… (More)
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