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Lukas Mehl
Lukas Mehl
Bestätigte E-Mail-Adresse bei vis.uni-stuttgart.de
Titel
Zitiert von
Zitiert von
Jahr
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
132023
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
122022
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
72022
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
62023
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
52021
Distracting Downpour: Adversarial Weather Attacks for Motion Estimation
J Schmalfuss, L Mehl, A Bruhn
arXiv preprint arXiv:2305.06716, 2023
22023
Attacking Motion Estimation with Adversarial Snow
J Schmalfuss, L Mehl, A Bruhn
arXiv preprint arXiv:2210.11242, 2022
22022
Anisotropic selection schemes for order-adaptive variational optical flow methods
L Mehl
22020
Stereo Conversion With Disparity-Aware Warping, Compositing and Inpainting
L Mehl, A Bruhn, M Gross, C Schroers
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
2024
MS-RAFT+: High Resolution Multi-Scale RAFT
A Jahedi, M Luz, M Rivinius, L Mehl, A Bruhn
International Journal of Computer Vision, 1-22, 2023
2023
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
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