| Mot20: A benchmark for multi object tracking in crowded scenes P Dendorfer arXiv preprint arXiv:2003.09003, 2020 | 772 | 2020 |
| HOTA: A Higher Order Metric for Evaluating Multi-object Tracking L Jonathon, O Aljos̆a, P Dendorfer, P Torr, A Geiger, L Leal-Taixé, ... International Journal of Computer Vision 129 (2), 548-578, 2021 | 719* | 2021 |
| Motchallenge: A benchmark for single-camera multiple target tracking P Dendorfer, A Osep, A Milan, K Schindler, D Cremers, I Reid, S Roth, ... International Journal of Computer Vision 129, 845-881, 2021 | 288* | 2021 |
| Goal-gan: Multimodal trajectory prediction based on goal position estimation P Dendorfer, A Osep, L Leal-Taixé Proceedings of the Asian Conference on Computer Vision, 2020 | 120 | 2020 |
| CVPR19 tracking and detection challenge: How crowded can it get? P Dendorfer, H Rezatofighi, A Milan, J Shi, D Cremers, I Reid, S Roth, ... arXiv preprint arXiv:1906.04567, 2019 | 107 | 2019 |
| Mg-gan: A multi-generator model preventing out-of-distribution samples in pedestrian trajectory prediction P Dendorfer, S Elflein, L Leal-Taixé Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 98 | 2021 |
| Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking? P Dendorfer, V Yugay, A Ošep, L Leal-Taixé Conference on Neural Information Processing Systems, 2022 | 36 | 2022 |
| MOTCOM: The multi-object tracking dataset complexity metric M Pedersen, JB Haurum, P Dendorfer, TB Moeslund European Conference on Computer Vision, 20-37, 2022 | 2 | 2022 |
| Deep Learning for Human Motion: Advancing Trajectory Prediction and Multi-Object Tracking P Dendorfer Technische Universität München, 2023 | | 2023 |
Laura Leal-TaixéSenior Research Manager at NVIDIA. Prev. Prof. TU MunichVerified email at tum.de
