| Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo L Mehl, J Schmalfuss, A Jahedi, Y Nalivayko, A Bruhn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 10 | 2023 |
| Multi-scale RAFT: Combining hierarchical concepts for learning-based optical flow estimation A Jahedi, L Mehl, M Rivinius, A Bruhn 2022 IEEE International Conference on Image Processing (ICIP), 1236-1240, 2022 | 8 | 2022 |
| M-FUSE: Multi-frame fusion for scene flow estimation L Mehl, A Jahedi, J Schmalfuss, A Bruhn Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 5 | 2023 |
| An anisotropic selection scheme for variational optical flow methods with order-adaptive regularisation L Mehl, C Beschle, A Barth, A Bruhn International Conference on Scale Space and Variational Methods in Computer …, 2021 | 5 | 2021 |
| High resolution multi-scale RAFT (Robust Vision Challenge 2022) A Jahedi, M Luz, L Mehl, M Rivinius, A Bruhn arXiv preprint arXiv:2210.16900, 2022 | 4 | 2022 |
| Distracting Downpour: Adversarial Weather Attacks for Motion Estimation J Schmalfuss, L Mehl, A Bruhn arXiv preprint arXiv:2305.06716, 2023 | 2 | 2023 |
| Anisotropic selection schemes for order-adaptive variational optical flow methods L Mehl | 2 | 2020 |
| Attacking Motion Estimation with Adversarial Snow J Schmalfuss, L Mehl, A Bruhn arXiv preprint arXiv:2210.11242, 2022 | 1 | 2022 |
| Replication Data for: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation L Mehl, C Beschle, A Barth, A Bruhn DaRUS, 2022 | | 2022 |
Andres BruhnProfessor of Computer Science, University of Stuttgart, GermanyEmail confirmado em vis.uni-stuttgart.de
