Matching
Description:
Matching is the problem of finding correspondences between two or more entities. It appears in computer vision as shape matching, i.e., finding correspondences between two 3D surfaces, as feature matching, i.e., finding correspondences between keypoints of similar but different objects, and as dense matching, i.e., finding dense correspondences of the same scene from different viewpoints. In optimization, this problem has theoretical formulations as the classic linear and quadratic assignment problems. We develop efficient algorithms that quickly and accurately solve correspondence problems and, when embedded in neural networks, deliver high-quality empirical results.
Literatur:
- "A Comparative Study of Graph Matching Algorithms in Computer Vision", Haller, Stefan and Feineis, Lorenz and Hutschenreiter, Lisa and Bernard, Florian and Rother, Carsten and Kainmuller, Dagmar and Swoboda, Paul and Savchynskyy, Bogdan, IEEE European Conference on Computer Vision (ECCV) 2022
- "A Scalable Combinatorial Solver for Elastic Geometrically Consistent 3D Shape Matching", Roetzer, Paul and Swoboda, Paul and Cremers, Daniel and Bernard, Florian, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022
- "Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers", Rolínek, Michal and Swoboda, Paul and Zietlow, Dominik and Paulus, Anselm and Musil, Vít and Martius, Georg, Proceedings of the IEEE European Conference on Computer Vision (ECCV) 2020
- "Higher-order Projected Power Iterations for Scalable Multi-Matching", Bernard, Florian and Thunberg, Johan and Swoboda, Paul and Theobalt, Christian, Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2019
- "A Convex Relaxation for Multi-Graph Matching", Swoboda, Paul and Mokarian, Ashkan and Theobalt, Christian and Bernard, Florian and others, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019
- "A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching"Swoboda, Paul and Rother, Carsten and Abu Alhaija, Hassan and Kainmuller, Dagmar and Savchynskyy, Bogdan, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017