Bogdan Savchynskyy

According to our database, Bogdan Savchynskyy authored at least 36 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Discrete Cycle-Consistency Based Unsupervised Deep Graph Matching.

Siddharth Tourani, Muhammad Haris Khan, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Unsupervised Deep Graph Matching Based on Cycle Consistency.

Siddharth Tourani, Carsten Rother, Muhammad Haris Khan, Bogdan Savchynskyy

CoRR, 2023

Relative-Interior Solution for (Incomplete) Linear Assignment Problem with Applications to Quadratic Assignment Problem.

Tomás Dlask, Bogdan Savchynskyy

CoRR, 2023

2022

Structured Prediction Problem Archive.

Paul Swoboda, Andrea Hornáková, Paul Roetzer, Bogdan Savchynskyy, Ahmed Abbas

CoRR, 2022

A Comparative Study of Graph Matching Algorithms in Computer Vision.

Stefan Haller, Lorenz Feineis, Lisa Hutschenreiter, Florian Bernard, Carsten Rother, Dagmar Kainmüller, Paul Swoboda, Bogdan Savchynskyy

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Fusion Moves for Graph Matching.

Lisa Hutschenreiter, Stefan Haller, Lorenz Feineis, Carsten Rother, Dagmar Kainmüller, Bogdan Savchynskyy

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

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

Siddharth Tourani, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Primal-Dual Solver for Large-Scale Tracking-by-Assignment.

Stefan Haller, Mangal Prakash, Lisa Hutschenreiter, Tobias Pietzsch, Carsten Rother, Florian Jug, Paul Swoboda, Bogdan Savchynskyy

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Discrete Graphical Models - An Optimization Perspective.

Bogdan Savchynskyy

Found. Trends Comput. Graph. Vis., 2019

2018

Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction.

Anurag Arnab, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H. S. Torr

IEEE Signal Process. Mag., 2018

Maximum Persistency via Iterative Relaxed Inference in Graphical Models.

Alexander Shekhovtsov, Paul Swoboda, Bogdan Savchynskyy

IEEE Trans. Pattern Anal. Mach. Intell., 2018

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

Siddharth Tourani, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Computer Vision - ECCV 2018, 2018

Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation.

Stefan Haller, Paul Swoboda, Bogdan Savchynskyy

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Towards Globally Optimal Normal Orientations for Large Point Clouds.

Nico Schertler, Bogdan Savchynskyy, Stefan Gumhold

Comput. Graph. Forum, 2017

A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching.

Paul Swoboda, Carsten Rother, Hassan Abu Alhaija, Dagmar Kainmüller, Bogdan Savchynskyy

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems.

Paul Swoboda, Jan Kuske, Bogdan Savchynskyy

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Global Hypothesis Generation for 6D Object Pose Estimation.

Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

InstanceCut: From Edges to Instances with MultiCut.

Alexander Kirillov, Evgeny Levinkov, Bjoern Andres, Bogdan Savchynskyy, Carsten Rother

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

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

Paul Swoboda, Alexander Shekhovtsov, Jörg Hendrik Kappes, Christoph Schnörr, Bogdan Savchynskyy

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Multicuts and Perturb & MAP for Probabilistic Graph Clustering.

Jörg Hendrik Kappes, Paul Swoboda, Bogdan Savchynskyy, Tamir Hazan, Christoph Schnörr

J. Math. Imaging Vis., 2016

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

Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Joint Training of Generic CNN-CRF Models with Stochastic Optimization.

Alexander Kirillov, Dmitrij Schlesinger, Shuai Zheng, Bogdan Savchynskyy, Philip H. S. Torr, Carsten Rother

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.

Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kröger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, Carsten Rother

Int. J. Comput. Vis., 2015

Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts.

Jörg Hendrik Kappes, Paul Swoboda, Bogdan Savchynskyy, Tamir Hazan, Christoph Schnörr

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

M-Best-Diverse Labelings for Submodular Energies and Beyond.

Alexander Kirillov, Dmytro Shlezinger, Dmitry P. Vetrov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Inferring M-Best Diverse Labelings in a Single One.

Alexander Kirillov, Bogdan Savchynskyy, Dmitrij Schlesinger, Dmitry P. Vetrov, Carsten Rother

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

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

Paul Swoboda, Bogdan Savchynskyy, Jörg H. Kappes, Christoph Schnörr

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Partial Optimality via Iterative Pruning for the Potts Model.

Paul Swoboda, Bogdan Savchynskyy, Jörg H. Kappes, Christoph Schnörr

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2013

Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation.

Bogdan Savchynskyy, Jörg Hendrik Kappes, Paul Swoboda, Christoph Schnörr

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Getting Feasible Variable Estimates from Infeasible Ones: MRF Local Polytope Study.

Bogdan Savchynskyy, Stefan Schmidt

Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

2012

Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing.

Bogdan Savchynskyy, Stefan Schmidt, Jörg H. Kappes, Christoph Schnörr

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

A bundle approach to efficient MAP-inference by Lagrangian relaxation.

Jörg Hendrik Kappes, Bogdan Savchynskyy, Christoph Schnörr

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization.

Stefan Schmidt, Bogdan Savchynskyy, Jörg H. Kappes, Christoph Schnörr

Proceedings of the Energy Minimazation Methods in Computer Vision and Pattern Recognition, 2011

A study of Nesterov's scheme for Lagrangian decomposition and MAP labeling.

Bogdan Savchynskyy, Jörg H. Kappes, Stefan Schmidt, Christoph Schnörr

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2008

Discriminative Learning of Max-Sum Classifiers.

Vojtech Franc, Bogdan Savchynskyy

J. Mach. Learn. Res., 2008

2006

Character templates learning for textual images recognition as an example of learning in structural recognition.

Bogdan Savchynskyy, Olexander Kamotskyy

Proceedings of the Second International Workshop on Document Image Analysis for Libraries (DIAL 2006), 2006