A Survey on Deep Domain Adaptation for LiDAR Perception LT Triess, M Dreissig, CB Rist, JM Zöllner Workshop Autonomy@Scale, 2021 IEEE Intelligent Vehicles Symposium (IV), 2021 | 64 | 2021 |
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study LT Triess, D Peter, CB Rist, JM Zöllner 2020 IEEE Intelligent Vehicles Symposium (IV), 1116-1121, 2020 | 46 | 2020 |
CNN-based synthesis of realistic high-resolution LiDAR data LT Triess, D Peter, CB Rist, M Enzweiler, JM Zöllner 2019 IEEE Intelligent Vehicles Symposium (IV), 2019 | 12 | 2019 |
Point Cloud Generation with Continuous Conditioning LT Triess, A Bühler, D Peter, FB Flohr, JM Zöllner International Conference on Artificial Intelligence and Statistics (AISTATS …, 2022 | 9 | 2022 |
A Realism Metric for Generated LiDAR Point Clouds LT Triess, CB Rist, D Peter, JM Zöllner International Journal of Computer Vision 130 (12), 2962-2979, 2022 | 5 | 2022 |
Quantifying point cloud realism through adversarially learned latent representations LT Triess, D Peter, SA Baur, JM Zöllner 2021 German Conference on Pattern Recognition (GCPR), 2021 | 2 | 2021 |
Semi-Local Convolutions for LiDAR Scan Processing LT Triess, D Peter, JM Zöllner I (Still) Can't Believe It's Not Better! NeurIPS 2021 Workshop, 2021 | 2 | 2021 |
LiDAR Domain Adaptation-Automotive 3D Scene Understanding LT Triess | | 2023 |