M2p3: multimodal multi-pedestrian path prediction by self-driving cars with egocentric vision A Poibrenski, M Klusch, I Vozniak, C Müller Proceedings of the 35th Annual ACM Symposium on Applied Computing, 190-197, 2020 | 32 | 2020 |
Multimodal multi-pedestrian path prediction for autonomous cars A Poibrenski, M Klusch, I Vozniak, C Müller ACM SIGAPP Applied Computing Review 20 (4), 5-17, 2021 | 14 | 2021 |
Towards a methodology for training with synthetic data on the example of pedestrian detection in a frame-by-frame semantic segmentation task A Poibrenski, J Sprenger, C Müller Proceedings of the 1st International Workshop on Software Engineering for AI …, 2018 | 11 | 2018 |
Simp3: Social interaction-based multi-pedestrian path prediction by self-driving cars N Muscholl, A Poibrenski, M Klusch, P Gebhard 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2731-2738, 2020 | 7 | 2020 |
Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection F Nozarian, S Agarwal, F Rezaeianaran, D Shahzad, A Poibrenski, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 1 | 2023 |
How machine perception relates to human perception: visual saliency and distance in a frame-by-frame semantic segmentation task for highly/fully automated driving N Herbig, F Wiehr, A Poibrenski, J Sprenger, C Müller Proceedings of the 1st International Workshop on Software Engineering for AI …, 2018 | 1 | 2018 |
Uncertainty-aware pseudo labels for domain adaptation in pedestrian trajectory prediction A Poibrenski, F Nozarian, F Rezaeianaran, C Müller 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | | 2023 |
M2P3 A Poibrenski, M Klusch, I Vozniak, C Müller Proceedings of the 35th Annual ACM Symposium on Applied Computing, 2020 | | 2020 |