ResearchBlog‎ > ‎

Several GraphCut papers to read

posted Sep 30, 2014, 8:29 AM by Teng-Yok Lee   [ updated Sep 30, 2014, 8:29 AM ]
These papers are the suggestion to-read list of the Coursera course Discrete Inference and Learning in Artificial Vision (instructors: Nikos Paragios and Pawan Kumar)

Chaohui Wang, Nikos Komodakis, Nikos ParagiosMarkov Random Field modeling, inference & learning in computer vision & image understanding: A surveyComputer Vision and Image Understanding 117(11): 1610-1627 (2013)
Yuri Boykov and Vladimir KolmogorovAn Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in VisionIEEE Transactions on Pattern Analysis and Machine Intelligence, 26(9):1124-1137 (2004)
Yuri Boykov and Olga VekslerGraph Cuts in Vision and Graphics: Theories and ApplicationsHandbook of Mathematical Models in Computer Vision, edited by Nikos Paragios, Yunmei Chen and Olivier Faugeras. Springer, 2006
Yuri Boykov, Olga Veksler and Ramin ZabihFast Approximate Energy Minimization via Graph CutsIEEE Transactions on Pattern Analysis and Machine Inteligence, 23(11): 1222-1239 (2001)
Vladimir KolmogorovConvergent Tree-reweighted Message Passing for Energy MinimizationIEEE Transactions on Pattern Analysis and Machine Intelligence 28(10): 1568-1583 (2006)
Vladimir Kolmogorov and Ramin ZabihWhat Energy Functions can be Minimized via Graph Cuts?IEEE Transactions on Pattern Analysis and Machine Inteligence, 26(2): 147-159 (2004)
Nikos Komodakis, Georgios Tziritas, Nikos ParagiosPerformance vs computational efficiency for optimizing single and dynamic MRFs: Setting the state of the art with primal-dual strategiesComputer Vision and Image Understanding 112(1), 14-29 (2008)
Nikos Komodakis, Nikos Paragios, Georgios TziritasMRF Energy Minimization and Beyond via Dual DecompositionIEEE Transactions on Pattern Analysis Machine Intelligence 33(3): 531-552 (2011)
Ben Taskar, Carlos Guestrin and Daphne KollerMax-Margin Markov NetworksProceedings of Advances in Neural Information Processing Systems: (2003)
Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann and Yasmine AltunLarge Margin Methods for Structured and Interdependent Output VariablesJournal of Machine Learning Research, 6:1453-1484 (2005)
Tomas WernerRevisiting the Linear Programming Relaxation Approach to Gibbs Energy Minimization and Weighted Constraint SatisfactionIEEE Transactions on Pattern Analysis and Machine Intelligence 32(8): 1474-1488 (2010)