V. Kolmogorov

Publications129
h-index46
Citations27,610
Highly Influential Citations2,707
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"GrabCut": interactive foreground extraction using iterated graph cuts
TLDR
The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Expand
  • 4,537
  • 789
  • PDF
An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision
TLDR
Minimum cut/maximum flow algorithms on graphs have emerged as an increasingly useful tool for exactor approximate energy minimization in low-level vision. Expand
  • 3,359
  • 246
  • PDF
Convergent Tree-Reweighted Message Passing for Energy Minimization
  • V. Kolmogorov
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 October 2006
TLDR
In this paper, we focus on the recent technique proposed by Wainwright et al. (Nov. 2005)- tree-reweighted max-product message passing (TRW). Expand
  • 1,271
  • 222
  • PDF
What Energy Functions Can Be Minimized via Graph Cuts?
TLDR
We give a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables. Expand
  • 2,293
  • 166
Computing visual correspondence with occlusions using graph cuts
TLDR
We present a new graph cut algorithm for visual correspondence that handles occlusions properly, while maintaining the key advantages of graph cuts. Expand
  • 1,256
  • 123
  • PDF
What energy functions can be minimized via graph cuts?
  • V. Kolmogorov, R. Zabih
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 28 May 2002
TLDR
We give a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables. Expand
  • 1,619
  • 109
  • PDF
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
TLDR
This paper provides an experimental comparison of the efficiency of min-cut/max flow algorithms for applications in low-level vision. Expand
  • 2,102
  • 94
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
TLDR
We describe a set of energy minimization benchmarks and use them to compare the solution quality and runtime of several commonenergy minimization algorithms. Expand
  • 1,018
  • 91
  • PDF
Multi-camera Scene Reconstruction via Graph Cuts
TLDR
We address the problem of computing the 3-dimensional shape of an arbitrary scene from a set of images taken at known viewpoints. Expand
  • 853
  • 91
  • PDF
Optimizing Binary MRFs via Extended Roof Duality
TLDR
We present an efficient implementation of the "probing" technique introduced recently by Bows et al. (2006). Expand
  • 490
  • 73
  • PDF