| The ind dataset: A drone dataset of naturalistic road user trajectories at german intersections J Bock, R Krajewski, T Moers, S Runde, L Vater, L Eckstein 2020 IEEE Intelligent Vehicles Symposium (IV), 1929-1934, 2020 | 373 | 2020 |
| The round dataset: A drone dataset of road user trajectories at roundabouts in germany R Krajewski, T Moers, J Bock, L Vater, L Eckstein 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 162 | 2020 |
| Social emotion mining techniques for Facebook posts reaction prediction F Krebs, B Lubascher, T Moers, P Schaap, G Spanakis arXiv preprint arXiv:1712.03249, 2017 | 76 | 2017 |
| The exid dataset: A real-world trajectory dataset of highly interactive highway scenarios in germany T Moers, L Vater, R Krajewski, J Bock, A Zlocki, L Eckstein 2022 IEEE Intelligent Vehicles Symposium (IV), 958-964, 2022 | 61 | 2022 |
| Data-driven maneuver modeling using generative adversarial networks and variational autoencoders for safety validation of highly automated vehicles R Krajewski, T Moers, D Nerger, L Eckstein 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 59 | 2018 |
| Béziervae: Improved trajectory modeling using variational autoencoders for the safety validation of highly automated vehicles R Krajewski, T Moers, A Meister, L Eckstein 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 3788-3795, 2019 | 18 | 2019 |
| SEMTec: social emotion mining techniques for analysis and prediction of facebook post reactions T Moers, F Krebs, G Spanakis Agents and Artificial Intelligence: 10th International Conference, ICAART …, 2019 | 13 | 2019 |
| Highly accurate scenario and reference data for automated driving J Bock, L Vater, R Krajewski, T Moers ATZ worldwide 123 (5), 50-55, 2021 | 8 | 2021 |
| VeGAN: Using GANs for augmentation in latent space to improve the semantic segmentation of vehicles in images from an aerial perspective R Krajewski, T Moers, L Eckstein 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 1440-1448, 2019 | 7 | 2019 |
| Utilization and Potentials of Unmanned Aerial Vehicles (UAVs) in the Field of Automated Driving: A Survey L Kloeker, T Moers, L Vater, A Zlocki, L Eckstein 2021 5th International Conference on Vision, Image and Signal Processing …, 2021 | 2 | 2021 |
| Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles R Krajewski, L Vater, M Klimke, T Moers, J Bock, L Eckstein 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 1 | 2021 |
| A Semi-Automated Corner Case Detection and Evaluation Pipeline I Tulleners, T Moers, T Schulik, M Sedlacek arXiv preprint arXiv:2305.16369, 2023 | | 2023 |
| Method, apparatus and computer program for enabling a sensor system for detecting objects in an environment of a vehicle M Ruchti, T Nägele, S Rinkenauer, J Klimke, T Moers, D Raudszus, ... US Patent App. 17/775,048, 2022 | | 2022 |
| Hochgenaue Szenarien-und Referenzdaten für das automatisierte Fahren J Bock, L Vater, R Krajewski, T Moers ATZ-Automobiltechnische Zeitschrift 123 (5), 50-55, 2021 | | 2021 |
Robert KrajewskiInstitute for Automotive Engineering, RWTH Aachen UniversityVerified email at ika.rwth-aachen.de
