What the constant velocity model can teach us about pedestrian motion prediction C Schöller, V Aravantinos, F Lay, A Knoll IEEE Robotics and Automation Letters 5 (2), 1696-1703, 2020 | 243* | 2020 |
Providentia-a large-scale sensor system for the assistance of autonomous vehicles and its evaluation A Krämmer, C Schöller, D Gulati, V Lakshminarasimhan, F Kurz, ... Journal of Field Robotics, 2022 | 71 | 2022 |
Targetless Rotational Auto-Calibration of Radar and Camera for Intelligent Transportation Systems C Schöller, M Schnettler, A Krämmer, G Hinz, M Bakovic, M Güzet, A Knoll Intelligent Transportation Systems Conference (ITSC), 2019 | 43 | 2019 |
Flomo: Tractable motion prediction with normalizing flows C Schöller, A Knoll 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 15 | 2021 |
Risk-based safety envelopes for autonomous vehicles under perception uncertainty J Bernhard, P Hart, A Sahu, C Schöller, MG Cancimance 2022 IEEE Intelligent Vehicles Symposium (IV), 104-111, 2022 | 10 | 2022 |
Vorausschauende Wahrnehmung für sicheres automatisiertes Fahren A Krämmer, C Schöller, F Kurz, D Rosenbaum, A Knoll Internationales verkehrswesen, 2020 | 3 | 2020 |
Towards Real-time Lifetime Prediction of Information Diffusion I Taxidou, A Alzoghbi, PM Fischer, C Schöller Proceedings of the ACM Web Science Conference, 1-2, 2015 | 2 | 2015 |
Robust and Probabilistic Motion Prediction for Intelligent Infrastructure Systems C Schöller Technische Universität München, 2022 | | 2022 |
Providentia - A Large Scale Sensing System for the Assistance of Autonomous Vehicles A Krämmer, C Schöller, D Gulati, A Knoll Robotics: Science and Systems (RSS), Workshop on Scene and Situation …, 2019 | | 2019 |