RegNet: Multimodal sensor registration using deep neural networks N Schneider, F Piewak, C Stiller, U Franke 2017 IEEE intelligent vehicles symposium (IV), 1803-1810, 2017 | 131 | 2017 |
Cnn-based lidar point cloud de-noising in adverse weather R Heinzler, F Piewak, P Schindler, W Stork IEEE Robotics and Automation Letters 5 (2), 2514-2521, 2020 | 93 | 2020 |
Boosting lidar-based semantic labeling by cross-modal training data generation F Piewak, P Pinggera, M Schafer, D Peter, B Schwarz, N Schneider, ... Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 53 | 2018 |
Fully convolutional neural networks for dynamic object detection in grid maps F Piewak, T Rehfeld, M Weber, JM Zöllner 2017 IEEE Intelligent Vehicles Symposium (IV), 392-398, 2017 | 23 | 2017 |
Analyzing the cross-sensor portability of neural network architectures for LiDAR-based semantic labeling F Piewak, P Pinggera, M Zöllner 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 3419-3426, 2019 | 8 | 2019 |
Improved semantic stixels via multimodal sensor fusion F Piewak, P Pinggera, M Enzweiler, D Pfeiffer, M Zöllner Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019 | 8 | 2019 |
LiDAR-based Semantic Labeling: Automotive 3D Scene Understanding FPJ Piewak | 2 | 2020 |
Survey on LiDAR Perception in Adverse Weather Conditions M Dreissig, D Scheuble, F Piewak, J Boedecker arXiv preprint arXiv:2304.06312, 2023 | | 2023 |
On the calibration of underrepresented classes in LiDAR-based semantic segmentation M Dreissig, F Piewak, J Boedecker arXiv preprint arXiv:2210.06811, 2022 | | 2022 |