Follow
Paul Swoboda
Title
Cited by
Cited by
Year
Lifted disjoint paths with application in multiple object tracking
A Hornakova, R Henschel, B Rosenhahn, P Swoboda
International conference on machine learning, 4364-4375, 2020
1532020
Deep graph matching via blackbox differentiation of combinatorial solvers
M Rolínek, P Swoboda, D Zietlow, A Paulus, V Musil, G Martius
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
1142020
A study of lagrangean decompositions and dual ascent solvers for graph matching
P Swoboda, C Rother, H Abu Alhaija, D Kainmuller, B Savchynskyy
Proceedings of the IEEE conference on computer vision and pattern …, 2017
642017
A convex relaxation for multi-graph matching
P Swoboda, A Mokarian, C Theobalt, F Bernard
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
472019
Making higher order mot scalable: An efficient approximate solver for lifted disjoint paths
A Hornakova, T Kaiser, P Swoboda, M Rolinek, B Rosenhahn, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
442021
A message passing algorithm for the minimum cost multicut problem
P Swoboda, B Andres
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
372017
Partial Optimality by Pruning for MAP-Inference with General Graphical Models
P Swoboda, A Shekhovtsov, JH Kappes, C Schnörr, B Savchynskyy
IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (7), 1370 …, 2015
372015
Hippi: Higher-order projected power iterations for scalable multi-matching
F Bernard, J Thunberg, P Swoboda, C Theobalt
Proceedings of the ieee/cvf international conference on computer vision …, 2019
342019
Lmgp: Lifted multicut meets geometry projections for multi-camera multi-object tracking
DMH Nguyen, R Henschel, B Rosenhahn, D Sonntag, P Swoboda
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
332022
A dual ascent framework for Lagrangean decomposition of combinatorial problems
P Swoboda, J Kuske, B Savchynskyy
Proceedings of the IEEE conference on computer vision and pattern …, 2017
322017
Maximum Persistency via Iterative Relaxed Inference with Graphical Models
A Shekhovtsov, P Swoboda, B Savchynskyy
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
322015
Global MAP-optimality by shrinking the combinatorial search area with convex relaxation
B Savchynskyy, JH Kappes, P Swoboda, C Schnörr
Advances in Neural Information Processing Systems 26, 2013
322013
Convex variational image restoration with histogram priors
P Swoboda, C Schnörr
SIAM Journal on Imaging Sciences 6 (3), 1719-1735, 2013
262013
Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching
D MH Nguyen, H Nguyen, N Diep, TN Pham, T Cao, B Nguyen, ...
Advances in Neural Information Processing Systems 36, 2024
242024
Partial optimality via iterative pruning for the Potts model
P Swoboda, B Savchynskyy, J Kappes, C Schnörr
Scale Space and Variational Methods in Computer Vision: 4th International …, 2013
232013
Probabilistic correlation clustering and image partitioning using perturbed multicuts
JH Kappes, P Swoboda, B Savchynskyy, T Hazan, C Schnörr
Scale Space and Variational Methods in Computer Vision: 5th International …, 2015
202015
A comparative study of graph matching algorithms in computer vision
S Haller, L Feineis, L Hutschenreiter, F Bernard, C Rother, D Kainmüller, ...
European Conference on Computer Vision, 636-653, 2022
192022
Efficient message passing for 0–1 ILPs with binary decision diagrams
JH Lange, P Swoboda
International Conference on Machine Learning, 6000-6010, 2021
182021
MAP inference via block-coordinate Frank-Wolfe algorithm
P Swoboda, V Kolmogorov
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
182019
Exact map-inference by confining combinatorial search with LP relaxation
S Haller, P Swoboda, B Savchynskyy
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
182018
The system can't perform the operation now. Try again later.
Articles 1–20