Alexander Shekhovtsov

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Vaclav Hlavac (Václav Hlaváč)Professor of engineering cybernetics, Czech Technical university in PragueVerified email at cvut.cz
Boris FlachAssociate Professor, Czech Technical University in PragueVerified email at cmp.felk.cvut.cz
Carsten RotherProfessor Uni Heidelberg / GermanyVerified email at iwr.uni-heidelberg.de
Thomas PockProfessor of Computer Science, TU GrazVerified email at icg.tugraz.at
Patrick KnöbelreiterApplied Scientist at Amazon PrimeAirVerified email at amazon.at
Bogdan SavchynskyyGroup Leader at Heidelberg University, GermanyVerified email at iwr.uni-heidelberg.de
Pushmeet KohliDeepMindVerified email at google.com
Christian ReinbacherSenior Applied Scientist at Amazon PrimeAirVerified email at amazon.at
Dmitrij SchlesingerDresden University of TechnologyVerified email at tu-dresden.de
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
Vladimir KolmogorovIST AustriaVerified email at ist.ac.at
Paul SwobodaHeinrich-Heine Universität DüsseldorfVerified email at hhu.de
Viktor YanushBayesian Methods Research GroupVerified email at bayesgroup.ru
Siddharth TouraniPhD Student, University of HeidelbergVerified email at uni-heidelberg.de
Tomas PajdlaAssociate professor, Czech Technical University in PragueVerified email at cvut.cz
Michal Jancosekhttp://cmp.felk.cvut.cz/Verified email at jancosek.sk
Christian PayerGraz University of TechnologyVerified email at icg.tugraz.at
Alexander KirillovOpenAIVerified email at openai.com
Christoph SchnörrProfessor of Mathematics and Computer Science, Heidelberg UniversityVerified email at math.uni-heidelberg.de
Jörg Hendrik KappesHeidelberg EngineeringVerified email at math.uni-heidelberg.de

Alexander Shekhovtsov

Czech Technical University in Prague

Verified email at fel.cvut.cz - Homepage

machine learning deep learning statistical methods discrete variables


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Efficient MRF deformation model for non-rigid image matching A Shekhovtsov, I Kovtun, V Hlaváč Computer Vision and Image Understanding 112 (1), 91-99, 2008	215	2008
End-to-end training of hybrid CNN-CRF models for stereo P Knobelreiter, C Reinbacher, A Shekhovtsov, T Pock Proceedings of the IEEE conference on computer vision and pattern …, 2017	165	2017
On partial optimality in multi-label MRFs P Kohli, A Shekhovtsov, C Rother, V Kolmogorov, P Torr Proceedings of the 25th international conference on Machine learning, 480-487, 2008	91	2008
Scalable multi-view stereo M Jancosek, A Shekhovtsov, T Pajdla 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV …, 2009	50	2009
A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel ASV Hlavac International Journal of Computer Vision, 28, 2012	48*	2012
Automated integer programming based separation of arteries and veins from thoracic CT images C Payer, M Pienn, Z Bálint, A Shekhovtsov, E Talakic, E Nagy, ... Medical image analysis 34, 109-122, 2016	42	2016
Partial optimality by pruning for MAP-inference with general graphical models P Swoboda, A Shekhovtsov, JH Kappes, C Schnoerr, B Savchynskyy IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 38 (7), 1370–1382, 2016	37	2016
Curvature prior for MRF-based segmentation and shape inpainting A Shekhovtsov, P Kohli, C Rother Joint DAGM (German Association for Pattern Recognition) and OAGM Symposium …, 2012	37	2012
Maximum persistency via iterative relaxed inference with graphical models A Shekhovtsov, P Swoboda, S Bogdan IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (7), 1668-1682, 2018	32	2018
Feed-forward propagation in probabilistic neural networks with categorical and max layers A Shekhovtsov, B Flach International conference on learning representations, 2018	28*	2018
Generalized differentiable RANSAC T Wei, Y Patel, A Shekhovtsov, J Matas, D Barath Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023	27	2023
Complexity of discrete energy minimization problems M Li, A Shekhovtsov, D Huber Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016	27	2016
Belief propagation reloaded: Learning bp-layers for labeling problems P Knobelreiter, C Sormann, A Shekhovtsov, F Fraundorfer, T Pock Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	26	2020
Solving dense image matching in real-time using discrete-continuous optimization A Shekhovtsov, C Reinbacher, G Graber, T Pock arXiv preprint arXiv:1601.06274, 2016	24	2016
MPLP++: Fast, parallel dual block-coordinate ascent for dense graphical models S Tourani, A Shekhovtsov, C Rother, B Savchynskyy Proceedings of the European Conference on Computer Vision (ECCV), 251-267, 2018	22	2018
Maximum persistency in energy minimization A Shekhovtsov Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014	22	2014
VAE Approximation Error: ELBO and Exponential Families BF Alexander Shekhovtsov, Dmitrij Schlesinger International Conference on Learning Representations, 2022	20*	2022
Stochastic normalizations as bayesian learning A Shekhovtsov, B Flach Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019	19	2019
Path sample-analytic gradient estimators for stochastic binary networks A Shekhovtsov, V Yanush, B Flach Advances in neural information processing systems 33, 12884-12894, 2020	18	2020
Reintroducing straight-through estimators as principled methods for stochastic binary networks A Shekhovtsov, V Yanush DAGM German Conference on Pattern Recognition, 111-126, 2021	17	2021

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