Maximum Flows by Incremental Breadth-First Search

@inproceedings{Goldberg2011MaximumFB,
  title={Maximum Flows by Incremental Breadth-First Search},
  author={Andrew V. Goldberg and Sagi Hed and Haim Kaplan and Robert E. Tarjan and Renato F. Werneck},
  booktitle={ESA},
  year={2011}
}
Maximum flow and minimum s-t cut algorithms are used to solve several fundamental problems in computer vision. These problems have special structure, and standard techniques perform worse than the special-purpose Boykov-Kolmogorov (BK) algorithm. We introduce the incremental breadth-first search (IBFS) method, which uses ideas from BK but augments on shortest paths. IBFS is theoretically justified (runs in polynomial time) and usually outperforms BK on vision problems. 
Highly Influential
This paper has highly influenced 11 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 76 citations. REVIEW CITATIONS

From This Paper

Figures, tables, results, connections, and topics extracted from this paper.
41 Extracted Citations
28 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 41 extracted citations

77 Citations

01020'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 77 citations based on the available data.

See our FAQ for additional information.

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 28 references

Network Flows and Matching: First DIMACS Implementation Challenge

  • D. S. Johnson, C. C. McGeoch
  • 1993
Highly Influential
4 Excerpts

Kolmogorov . An Experimental Comparison of MinCut / MaxFlow Algorithms for Energy Minimization in Vision

  • Y. Boykov, V.
  • IEEE transactions on Pattern Analysis and Machine…
  • 2004

Similar Papers

Loading similar papers…