Anton Osokin
Anton Osokin
National Research University Higher School of Economics
Подтвержден адрес электронной почты в домене hse.ru - Главная страница
НазваниеПроцитированоГод
Fast approximate energy minimization with label costs
A Delong, A Osokin, HN Isack, Y Boykov
IJCV, International journal of computer vision 96 (1), 1-27, 2012
5062012
Fast approximate energy minimization with label costs
A Delong, A Osokin, HN Isack, Y Boykov
CVPR, Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2010
5062010
Tensorizing neural networks
A Novikov, D Podoprikhin, A Osokin, DP Vetrov
NIPS, Advances in Neural Information Processing Systems, 442-450, 2015
2282015
A principled deep random field model for image segmentation
P Kohli, A Osokin, S Jegelka
CVPR, Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
792013
Breaking Sticks and Ambiguities with Adaptive Skip-gram
S Bartunov, D Kondrashkin, A Osokin, D Vetrov
AISTATS, Proceedings of the International Conference on Artificial …, 2016
662016
Context-aware CNNs for person head detection
TH Vu, A Osokin, I Laptev
ICCV, Proceedings of the International Conference on Computer Vision, 2893-2901, 2015
552015
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
A Osokin, JB Alayrac, I Lukasewitz, PK Dokania, S Lacoste-Julien
ICML, Proceedings of the International Conference on Machine Learning, 2016
362016
GANs for Biological Image Synthesis
A Osokin, A Chessel, REC Salas, F Vaggi
ICCV, Proceedings of the International Conference on Computer Vision, 2017
272017
Submodular decomposition framework for inference in associative markov networks with global constraints
A Osokin, D Vetrov, V Kolmogorov
CVPR, Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2011
192011
Putting MRFs on a Tensor Train.
A Novikov, A Rodomanov, A Osokin, D Vetrov
ICML, Proceedings of the International Conference on Machine Learning, 811-819, 2014
172014
On structured prediction theory with calibrated convex surrogate losses
A Osokin, F Bach, S Lacoste-Julien
NIPS, Advances in Neural Information Processing Systems, 301-312, 2017
162017
Minimizing sparse high-order energies by submodular vertex-cover
A Delong, O Veksler, A Osokin, Y Boykov
NIPS, Advances in Neural Information Processing Systems, 962-970, 2012
132012
SEARNN: Training RNNs with Global-Local Losses
R Leblond, JB Alayrac, A Osokin, S Lacoste-Julien
arXiv preprint arXiv:1706.04499, 2017
112017
Perceptually inspired layout-aware losses for image segmentation
A Osokin, P Kohli
ECCV, Proceedings of the European Conference on Computer Vision, 663-678, 2014
92014
Submodular relaxation for MRFs with high-order potentials
A Osokin, D Vetrov
ECCV workshops, Proceedings of the workshops of European Conference on …, 2012
52012
Variational segmentation algorithms with label frequency constraints
D Kropotov, D Laptev, A Osokin, D Vetrov
Pattern Recognition and Image Analysis 20 (3), 324-334, 2010
52010
3-D mouse brain model reconstruction from a sequence of 2-D slices in application to Allen brain atlas
A Osokin, D Vetrov, D Kropotov
International Meeting on Computational Intelligence Methods for …, 2009
52009
Submodular relaxation for inference in Markov random fields
A Osokin, DP Vetrov
TPAMI, IEEE transactions on pattern analysis and machine intelligence 37 (7 …, 2015
42015
Modeling Spatio-Temporal Human Track Structure for Action Localization
G Chéron, A Osokin, I Laptev, C Schmid
arXiv preprint arXiv:1806.11008, 2018
12018
Deep Part-Based Generative Shape Model with Latent Variables
A Kirillov, M Gavrikov, E Lobacheva, A Osokin, D Vetrov
BMVC, Proceedings of the British Machine Vision Conference, 2016
12016
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Статьи 1–20