Visibility guided nms: Efficient boosting of amodal object detection in crowded traffic scenes N Gählert, N Hanselmann, U Franke, J Denzler NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving, 2020 | 18 | 2020 |
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients N Hanselmann, K Renz, K Chitta, A Bhattacharyya, A Geiger European Conference on Computer Vision (ECCV), 335–352, 2022 | 6 | 2022 |
Unsupervised Domain Adaptive Object Detection with Class Label Shift Weighted Local Features A Tan, N Hanselmann, S Ding, F Tombari, M Cordts Computer Vision–ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022 …, 2023 | | 2023 |
Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation N Hanselmann, N Schneider, B Ortelt, A Geiger IEEE Intelligent Vehicles Symposium (IV), 532-539, 2021 | | 2021 |
Supplementary Material for KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients N Hanselmann, K Renz, K Chitta, A Bhattacharyya, A Geiger | | |
Supplementary For: Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation N Hanselmann, N Schneider, B Ortelt, A Geiger | | |