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Florian Piewak
Florian Piewak
Mercedes-Benz AG, Daimler AG, Karlsruhe Institut of Technology (KIT)
Bestätigte E-Mail-Adresse bei mercedes-benz.com
Titel
Zitiert von
Zitiert von
Jahr
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
1662017
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
1202020
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
572018
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
242017
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
92019
Improved semantic stixels via multimodal sensor fusion
F Piewak, P Pinggera, M Enzweiler, D Pfeiffer, M Zöllner
German Conference on Pattern Recognition, 447-458, 2018
92018
Survey on LiDAR Perception in Adverse Weather Conditions
M Dreissig, D Scheuble, F Piewak, J Boedecker
arXiv preprint arXiv:2304.06312, 2023
32023
LiDAR-based Semantic Labeling: Automotive 3D Scene Understanding
FPJ Piewak
32020
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentation
M Dreissig, F Piewak, J Boedecker
arXiv preprint arXiv:2308.02248, 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
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