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Patrick Dendorfer
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Mot20: A benchmark for multi object tracking in crowded scenes
P Dendorfer, H Rezatofighi, A Milan, J Shi, D Cremers, I Reid, S Roth, ...
arXiv preprint arXiv:2003.09003, 2020
6892020
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
569*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
248*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
1102020
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
1002019
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
862021
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
302022
MOTCOM: The multi-object tracking dataset complexity metric
M Pedersen, JB Haurum, P Dendorfer, TB Moeslund
European Conference on Computer Vision, 20-37, 2022
22022
Deep Learning for Human Motion: Advancing Trajectory Prediction and Multi-Object Tracking
P Dendorfer
Technische Universität München, 2023
2023
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Articles 1–9