Jannik Quehl
Cited by
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Pointatme: efficient 3d point cloud labeling in virtual reality
F Wirth, J Quehl, J Ota, C Stiller
2019 IEEE Intelligent Vehicles Symposium (IV), 1693-1698, 2019
Driving like a human: Imitation learning for path planning using convolutional neural networks
E Rehder, J Quehl, C Stiller
International Conference on Robotics and Automation Workshops, 1-5, 2017
How good is my prediction? Finding a similarity measure for trajectory prediction evaluation
J Quehl, H Hu, ÖŞ Taş, E Rehder, M Lauer
2017 IEEE 20th International Conference on Intelligent Transportation …, 2017
An approach to vehicle trajectory prediction using automatically generated traffic maps
J Quehl, H Hu, S Wirges, M Lauer
2018 IEEE Intelligent Vehicles Symposium (IV), 544-549, 2018
LDFA: Latent Diffusion Face Anonymization for Self-driving Applications
M Klemp, K Rösch, R Wagner, J Quehl, M Lauer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
High definition mapping using lidar traced trajectories
S Busch, J Quehl, C Brenner
38. Wissenschaftlich-Technische Jahrestagung der DGPF und PFGK18 Tagung in …, 2018
Estimating Object Shape and Movement Using Local Occupancy Grid Maps
J Quehl, S Yan, S Wirges, JH Pauls, M Lauer
IFAC-PapersOnLine 52 (8), 87 - 92, 2019
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