no code implementations • CVPR 2023 • Harshil Bhatia, Edith Tretschk, Zorah Lähner, Marcel Seelbach Benkner, Michael Moeller, Christian Theobalt, Vladislav Golyanik
Jointly matching multiple, non-rigidly deformed 3D shapes is a challenging, $\mathcal{NP}$-hard problem.
no code implementations • 13 Oct 2022 • Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller, Vladislav Golyanik
As a result, the solution encodings can be chosen flexibly and compactly.
no code implementations • 24 Mar 2022 • Federica Arrigoni, Willi Menapace, Marcel Seelbach Benkner, Elisa Ricci, Vladislav Golyanik
Motion segmentation is a challenging problem that seeks to identify independent motions in two or several input images.
no code implementations • 8 Jul 2021 • Marcel Seelbach Benkner, Vladislav Golyanik, Christian Theobalt, Michael Moeller
In this work, we address such problems with emerging quantum computing technology and propose several reformulations of QAPs as unconstrained problems suitable for efficient execution on quantum hardware.
no code implementations • ICCV 2021 • Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Moeller
Finding shape correspondences can be formulated as an NP-hard quadratic assignment problem (QAP) that becomes infeasible for shapes with high sampling density.