Anton Osokin
Title
Cited by
Cited by
Year
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
6122012
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
6122010
Tensorizing neural networks
A Novikov, D Podoprikhin, A Osokin, DP Vetrov
NIPS, Advances in Neural Information Processing Systems, 442-450, 2015
5152015
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
1572016
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
1062015
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
892013
GANs for Biological Image Synthesis
A Osokin, A Chessel, REC Salas, F Vaggi
ICCV, Proceedings of the International Conference on Computer Vision, 2017
762017
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
672016
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
342017
SEARNN: Training RNNs with Global-Local Losses
R Leblond, JB Alayrac, A Osokin, S Lacoste-Julien
ICLR, Proceedings of International Conference on Learning Representations, 2018
302018
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
282014
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
242011
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
162012
Perceptually inspired layout-aware losses for image segmentation
A Osokin, P Kohli
ECCV, Proceedings of the European Conference on Computer Vision, 663-678, 2014
102014
Submodular relaxation for inference in Markov random fields
A Osokin, DP Vetrov
TPAMI, IEEE transactions on pattern analysis and machine intelligence 37 (7 …, 2015
82015
Submodular relaxation for MRFs with high-order potentials
A Osokin, D Vetrov
ECCV workshops, Proceedings of the workshops of European Conference on …, 2012
62012
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
62010
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
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
K Struminsky, S Lacoste-Julien, A Osokin
NIPS, Advances in Neural Information Processing Systems, 666-674, 2018
42018
OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features
A Osokin, D Sumin, V Lomakin
ECCV, Proceedings of European Conference on Computer Vision, 2020
32020
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Articles 1–20