RTEmagicC_people_sasha_02.jpg.jpg

Alexander (Oleksandr) Shekhovtsov

Postdoc

Czech Technical University in Prague

Faculty of Electrical Engineering

Department of Cybernetics

Center for Machiene Perception

Karlovo namesti 13, 121 35 Prague 2

Czech Republic

 

shekhovtsov@gmail.com

Qualification:

MSc. in applied mathematics from National Technical University of Ukraine “KPI”

Ph.D. in mathematical engineering from Czech Technical University in Prague

Research interests:

Discrete and continuous optimization with applications in computer vision. Markov random fields (energy minimization in computer vision). Machine learning.

Software:

Publications:

  • G. Munda, A. Shekhovtsov, P. Knöbelreiter, T. Pock (2017): Scalable Full Flow with Learned Binary Descriptors, GCPR, [arXiv]

  • A. Shekhovtsov, P. Swoboda and B. Savchynskyy (2017): Maximum Persistency via Iterative Relaxed Inference with Graphical Models, PAMI accepted [preprint] [code]

 

  • Knöbelreiter, P., Reinbacher, C., Shekhovtsov, A., and Pock, T. (2017). End-to-end training of hybrid CNN-CRF models for stereo. CVPR, to appear. [arXiv] [bib]

  • Li, M., Shekhovtsov, A., and Huber, D. (2016). Complexity of discrete energy minimization problems, ECCV. [arXiv] [spotlight] [bib]

  • Kirillov, A., Shekhovtsov, A., Rother, C., and Savchynskyy, B. (2016). Joint m-best-diverse labelings as a parametric submodular minimization. NIPS, [arXiv] [bib]

 

  • A. Shekhovtsov, C. Reinbacher, G. Graber and T. Pock: Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization, CVWW 2016 [pdf], [bib]

  • A. Shekhovtsov, P. Swoboda and B. Savchynskyy: Maximum Persistency via Iterative Relaxed Inference with Graphical Models, CVPR 2015 [pdf], [bib], [slides], [poster], code].

  • A. Shekhovtsov: Higher Order Maximum Persistency and Comparison Theorems, CVIU (SI on Inference & Learning of Graphical Models) 2014 [preprint].

  • A. Shekhovtsov: Maximum Persistency in Energy Minimization, CVPR 2014 [pdf], [bib], [slides]. Research Report [arXiv], [pdf], [bib].

  • A. Shekhovtsov: Exact and Partial Energy Minimization in Computer Vision, PhD Thesis, February 2013. [pdf], [bib], [slides].

  • A. Shekhovtsov, P. Kohli and C. Rother: Curvature Prior for MRF-Based Segmentation and Shape Inpainting, DAGM 2012. [pdf],[bib], [slides].

  • A. Shekhovtsov, V. Hlavac: A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel, IJCV 2012. [pdf], [bib], [slides], [code], [preprint].

  • A. Shekhovtsov, V. Hlavac: On Partial Opimality by Auxiliary Submodular Problems, Control Systems and Computers, 2011(2). [pdf], [bib].

  • A. Shekhovtsov, V. Hlavac: Joint Image GMM and Shading MAP Estimation, ICPR 2010. [pdf], [bib], Technical Report [pdf]

  • A. Shekhovtsov, V. Hlavac: A Lower Bound by One-against-all Decomposition for Potts Model Energy Minimization, CVVW 2008. [pdf], [bib], [slides]
     
  • P. Kohli, A. Shekhovtsov, C. Rother, V. Kolmogorov, P. Torr: On partial optimality in multi-label MRFs. ICML 2008: Proceedings of the 25th International Conference on Machine Learning. [pdf], [bib], [slides]

  • Shekhovtsov, J.D. Garcia-Arteaga, T. Werner: A Discrete Search Method for Multi-modal Non-Rigid Image Registration. NORDIA 2008: Proceedings of the 2008 IEEE CVPR Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment. [pdf], [bib], [slides]

  • Shekhovtsov, I. Kovtun, V. Hlavac: Efficient MRF Deformation Model for Non-Rigid Image Matching. CVIU 2008. [ScienceDirect]  ([preprint] / [ealier version]), [bib], [videos]

  • T. Werner, A. Shekhovtsov: Unified Framework for Semiring-Based Arc Consistency and Relaxation Labeling. Computer Vision Winter Workshop , St. Lambrecht, Austria, February 2007.

  • Shekhovtsov: Supermodular decomposition of structural labeling problem (in Russian). Control Systems and Computers #1, 2006, pp.39-48; Kiev, Ukraine. [pdf], [bib]

  • B. Flach, D. Schlesinger, A. Shekhovtsov: A Higher Order MRF-Model for Stereo-Reconstruction, Pattern Recognition, LNCS vol. 3175, 2004, 440-446. [link]

 

Technical Reports

  • A. Shekhovtsov, P. Kohli, C. Rother: Curvature Prior for MRF-based Segmentation and Shape Inpainting, Research Report CTU--CMP--2011--11, Czech Technical University. [pdf], [bib]

 

  • A. Shekhovtsov, V. Hlavac: A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel, Research Report K333--43/11, CTU--CMP--2011—03, Czech Technical University. [pdf], [bib]

  • A. Shekhovtsov, V. Hlavac: Joint Image GMM and Shading MAP Estimation, Research Report K333–35/10, CTU–CMP–2010–03, Czech Technical University.
    [pdf], [bib]

 

  • A. Shekhovtsov, V. Kolmogorov, P.Kohli, V. Hlavac, C. Rother, P. Torr: LP-relaxation of binarized energy minimization, Research Report CTU--CMP--2007—27, Czech Technical University, update 2008. [pdf], [bib]

 

 

 

voxelmrf

voxelmrf1

potts_hard

optimality

dual_shading

bnd2