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Global Hypothesis Generation for 6D Object Pose Estimation

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.115-124

2017

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InstanceCut: From Edges to Instances with MultiCut

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.7322-7331

2017

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Maximum Persistency via Iterative Relaxed Inference in Graphical Models

IEEE transactions on pattern analysis and machine intelligence, 2018-07, Vol.40 (7), p.1668-1682

2018

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Towards Globally Optimal Normal Orientations for Large Point Clouds

Computer graphics forum, 2017-01, Vol.36 (1), p.197-208

2017

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A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.4950-4960

2017

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

International journal of computer vision, 2015-11, Vol.115 (2), p.155-184

2015

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

IEEE transactions on pattern analysis and machine intelligence, 2016-07, Vol.38 (7), p.1370-1382

2016

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Inferring M-Best Diverse Labelings in a Single One

2015 IEEE International Conference on Computer Vision (ICCV), 2015, p.1814-1822

2015

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

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.7062-7071

2017

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Fusion Moves for Graph Matching

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.6250-6259

2021

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Maximum persistency via iterative relaxed inference with graphical models

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, p.521-529

2015

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Multicuts and Perturb & MAP for Probabilistic Graph Clustering

Journal of mathematical imaging and vision, 2016-10, Vol.56 (2), p.221-237

2016

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A bundle approach to efficient MAP-inference by Lagrangian relaxation

2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012, p.1688-1695

2012

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

CVPR 2011, 2011, p.1817-1823

2011

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A Comparative Study of Graph Matching Algorithms in Computer Vision

Computer Vision - ECCV 2022, 2022, Vol.13683, p.636-653

2022

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

2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014, p.1170-1177

2014

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

Computer Vision – ECCV 2018, p.264-281

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Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts

Scale Space and Variational Methods in Computer Vision, p.231-242

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Partial Optimality via Iterative Pruning for the Potts Model

Scale Space and Variational Methods in Computer Vision, p.477-488

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

2013 IEEE International Conference on Computer Vision Workshops, 2013, p.267-274

2013

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

Energy Minimization Methods in Computer Vision and Pattern Recognition, p.89-103

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

Second International Conference on Document Image Analysis for Libraries (DIAL'06), 2006, p.8 pp.-95

2006

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

IEEE signal processing magazine, 2018-01, Vol.35 (1), p.37-52

2018

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Global Hypothesis Generation for 6D Object Pose Estimation

InstanceCut: From Edges to Instances with MultiCut

Maximum Persistency via Iterative Relaxed Inference in Graphical Models

Towards Globally Optimal Normal Orientations for Large Point Clouds

A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems

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

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

Inferring M-Best Diverse Labelings in a Single One

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

Fusion Moves for Graph Matching

Maximum persistency via iterative relaxed inference with graphical models

Multicuts and Perturb & MAP for Probabilistic Graph Clustering

A bundle approach to efficient MAP-inference by Lagrangian relaxation

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

A Comparative Study of Graph Matching Algorithms in Computer Vision

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

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

Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts

Partial Optimality via Iterative Pruning for the Potts Model

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

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

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

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

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