Anton Osokin, PhD

PhD in mathematics (к.ф.-м.н.)
assistant in the department of Computational Mathematics and Cybernetics at the Moscow State University

In autumn, 2014 I'm moving to Paris to join INRIA-SIERRA project-team as a postdoc

E-mail: osokin -at- bayesgroup.ru

Research interests

  • Machine learning
  • Graphical models
  • Computer vision
  • Optimization

Selected publications

  • Anton Osokin, Pushmeet Kohli. Perceptually Inspired Layout-aware Losses for Image Segmentation. European Conference on Computer Vision (ECCV), 2014. pdf
  • PhD thesis: Submodular relaxation for energy minimization in Markov random fields, supervisor: Dr. Dmitry Vetrov (Lomonosov Moscow State University), May 2014. In Russian. text (pdf), synopsis (pdf)
  • Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry Vetrov. Putting MRFs on a Tensor Train. International Conference on Machine Learning (ICML), 2014. JMLR: W&CP volume 32. pdf, supplementary
  • Pushmeet Kohli, Anton Osokin, and Stefanie Jegelka. A Principled Deep Random Field Model for Image Segmentation. In Computer Vision and Pattern Recognition (CVPR), 2013. pdf, supplementary, code
  • Andrew Delong, Olga Veksler, Anton Osokin, and Yuri Boykov. Minimizing Sparse High-Order Energies by Submodular Vertex-Cover. Advances in Neural Information Processing Systems (NIPS), 2012. pdf
  • Anton Osokin, Dmitry Vetrov. Submodular Relaxation for MRFs with High-Order Potentials. HiPot: ECCV 2012 Workshop on Higher-Order Models and Global Constraints in Computer Vision, 2012. pdf + supplementary
  • Andrew Delong, Anton Osokin, Hossam Isack, and Yuri Boykov. Fast Approximate Energy Minimization with Label Costs, International Journal of Computer Vision (IJCV), 96(1):1–27, January 2012. pdf, code
  • Dmitry Vetrov, Anton Osokin. Graph Preserving Label Decomposition in Discrete MRFs with Selfish Potentials. Proceedings of International Workshop on Discrete Optimization in Machine learning (DISCML NIPS), December 2011. pdf
  • Anton Osokin, Dmitry Vetrov, and Vladimir Kolmogorov. Submodular Decomposition Framework for Inference in Associative Markov Networks with Global Constraints,
    In Computer Vision and Pattern Recognition (CVPR), June 2011. pdf
  • Andrew Delong, Anton Osokin, Hossam Isack, and Yuri Boykov. Fast Approximate Energy Minimization with Label Costs,
    In Computer Vision and Pattern Recognition (CVPR), June 2010. pdf, code

Code

Teaching