Alexander Shekhovtsov

发表

Normalization of Neural Networks using Analytic Variance Propagation pdf

Boris Flach, Alexander Shekhovtsov, 2018, ArXiv.

End-to-End Training of Hybrid CNN-CRF Models for Stereo

Thomas Pock, Alexander Shekhovtsov, Christian Reinbacher, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Scalable multi-view stereo

Tomás Pajdla, Alexander Shekhovtsov, Michal Jancosek, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Scalable Full Flow with Learned Binary Descriptors

Thomas Pock, Alexander Shekhovtsov, Patrick Knöbelreiter, 2017, GCPR.

A Higher Order MRF-Model for Stereo-Reconstruction

Dmitrij Schlesinger, Boris Flach, Alexander Shekhovtsov, 2004, DAGM-Symposium.

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization

Carsten Rother, Bogdan Savchynskyy, Alexander Kirillov, 2016, NIPS.

End-to-End Training of Hybrid CNN-CRF Models for Semantic Segmentation using Structured Learning

Aleksander Colovic, Thomas Pock, Alexander Shekhovtsov, 2017 .

A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel

Václav Hlavác, Alexander Shekhovtsov, A. Shekhovtsov, 2011, International Journal of Computer Vision.

Efficient MRF Deformation Model for Non-Rigid Image Matching

Václav Hlavác, Alexander Shekhovtsov, Ivan Kovtun, 2007, CVPR.

Stochastic Normalizations as Bayesian Learning

Boris Flach, Alexander Shekhovtsov, B. Flach, 2018, ACCV.

Curvature Prior for MRF-Based Segmentation and Shape Inpainting

Pushmeet Kohli, Carsten Rother, Alexander Shekhovtsov, 2011, DAGM/OAGM Symposium.

A discrete search method for multi-modal non-rigid image registration

Alexander Shekhovtsov, Tomás Werner, Juan D. García-Arteaga, 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

Feed-forward Uncertainty Propagation in Belief and Neural Networks pdf

Boris Flach, Alexander Shekhovtsov, Michal Busta, 2018, ArXiv.

Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems

Friedrich Fraundorfer, Thomas Pock, Alexander Shekhovtsov, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks pdf

Boris Flach, Alexander Shekhovtsov, Viktor Yanush, 2020, NeurIPS.

Complexity of Discrete Energy Minimization Problems

Daniel Huber, Alexander Shekhovtsov, Mengtian Li, 2016, ECCV.

Maximum persistency via iterative relaxed inference with graphical models

Bogdan Savchynskyy, Alexander Shekhovtsov, Paul Swoboda, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization

Alexander Shekhovtsov, Siddharth Tourani, Carsten Rother, 2020, AISTATS.

Partial Optimality by Pruning for MAP-Inference with General Graphical Models

Christoph Schnörr, Bogdan Savchynskyy, Jörg H. Kappes, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On Partial Opimality by Auxiliary Submodular Problems pdf

Václav Hlavác, Alexander Shekhovtsov, 2011, ArXiv.

Higher order maximum persistency and comparison theorems

Alexander Shekhovtsov, A. Shekhovtsov, 2015, Comput. Vis. Image Underst..

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models

Carsten Rother, Bogdan Savchynskyy, Alexander Shekhovtsov, 2018, ECCV.

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks pdf

Dmitry Vetrov, Alexander Shekhovtsov, Dmitry Molchanov, 2020, ArXiv.

Generative learning for deep networks pdf

Boris Flach, Alexander Shekhovtsov, Ondrej Fikar, 2017, ArXiv.

Automated integer programming based separation of arteries and veins from thoracic CT images

Michael Pienn, Christian Payer, Andrea Olschewski, 2016, Medical Image Anal..

Maximum Persistency in Energy Minimization

Alexander Shekhovtsov, A. Shekhovtsov, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Joint Image GMM and Shading MAP Estimation

Václav Hlavác, Alexander Shekhovtsov, 2010, 2010 20th International Conference on Pattern Recognition.

A Distributed Mincut/Maxflow Algorithm Combining Path Augmentation and Push-Relabel

Václav Hlavác, Alexander Shekhovtsov, 2011, EMMCVPR.

Efficient MRF Deformation Model for Non-Rigid Image Matching

Václav Hlavác, Alexander Shekhovtsov, Ivan Kovtun, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization pdf

Thomas Pock, Alexander Shekhovtsov, Gottfried Graber, 2016, ArXiv.

On partial optimality in multi-label MRFs

Vladimir Kolmogorov, Pushmeet Kohli, Carsten Rother, 2008, ICML '08.

Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers

Boris Flach, Alexander Shekhovtsov, B. Flach, 2018, ICLR.

Initialization and Transfer Learning of Stochastic Binary Networks from Real-Valued Ones

Alexander Shekhovtsov, Anastasiia Livochka, A. Shekhovtsov, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators pdf

Alexander Shekhovtsov, A. Shekhovtsov, 2021, GCPR.

SUPERMODULAR DECOMPOSITION OF STRUCTURAL LABELING PROBLEM

Alexander Shekhovtsov, A. Shekhovtsov, 2005 .