M.Sc. Frank Bieder

FZI Forschungszentrum Informatik
Haid-und-Neu-Str. 10–14
76131 Karlsruhe, Germany

Research

My research interest lies at the intersection of computer vision and machine learning in the context of mobile perception systems. Currently, I am working on deep learning methods for 3D scene understanding to enable map-less driving or self-localization in sparse planning maps. In particular, I am interested in exploring how to overcome data shortage by leveraging the 6D pose awareness of mobile systems in highly accurate semantic 3D maps . Exampels of my current research are:

Map Learning: Automatic data generation for deep learning applications using HD maps and multi-drive mapping
Leveraging Map Learning for self-localisation, semantic mapping and map-less driving
Learning-based 3D scene understanding

Teaching

Übungsleiter der Vorlesung Messtechnik II (SS20, WS20/21, SS21, WS21/22, SS22, WS22/23)
Aufgabensteller Grundlagen der Mess- und Regelungstechnik (SS19, WS19/20, SS20, SS21, WS21/22, WS22/23)
Mechatronik-Praktikum (WS19/20)
Rechnergestützte Verfahren in der Mess- und Regelungstechnik (WS19/20, WS20/21, WS21/22)

Academic Services

Reviewer for
- IEEE ITS Intelligent Vehicles Symposium (IV)
- IEEE ITS Intelligent Transportation Systems Magazine (ITS-M)
- IEEE RAS International Conference for Robotics and Automatisation (ICRA)
- IEEE RSJ International Conference on Intelligent Robots and Systems (IROS)
- IEEE RAS Robotics and Automation Letters (RA-L)
- Springer International Journal of Computer Vision (VISI)
- De Gruyter TM-Technisches Messen (TM)
Chair of workshop on Bridging the gap between map-based and map-less driving in the context of automated driving at Intelligent Vehicles Symposium (IV) 2022 in Aachen, Germany, and 2023 in Anchorage, USA.
Associate editor at Intelligent Vehicles Symposium (IV) 2022 in Anchorage, USA
Chair of special session on Real-time critical perception tasks in the context of automated driving at FUSION 2021 in Sun City, South Africa, and FUSION 2022 in Linköping, Sweden

Open Theses

Ground Truth Annotation for a Custom Autonomous Driving Dataset

Completed Theses

Recursive fusion of sequential LiDAR measurements considering dynamic occlusions for the creation of grid maps in the context of autonomous driving, master thesis March 2022
Automated Data Generation with HD-Maps for Machine Learning in the Context of Automated Driving, master thesis, April 2021
Occlusion Handling for Automatic Data Generation using HD Maps and a highly accurate SLAM, master thesis, November 2020
Fusion of Simultaneously Learned Semantic Information from Different Representations, master thesis, November 2020
A Comparison of Different Approaches to Solve the SLAM Problem on a Formula Student Driverless Race Car, master thesis, November 2020
Combining Sequential LiDAR Measurements For Semantic Segmentation of Multi-Layer Grid Maps, master thesis, November 2020
Panoptic Segmentation of Urban Scenarios, master thesis, September 2020

Publications

A Dual Evidential Top-View Representation to Model the Semantic Environment of Automated Vehicles
Richter, S.; Bieder, F.; Wirges, S.; Stiller, C.
2024. IEEE Transactions on Intelligent Vehicles, 9 (1), 2688–2700. doi:10.1109/TIV.2023.3284400
Ein Ansatz zur automatisierten Erstellung von Trainingsdaten unter Verwendung von HD-Karten und Mehrfachbefahrungen
Bieder, F.; Hu, H.; Schantz, J.; Kirik, O.; Ries, F.; Haueis, M.; Stiller, C.
2023. Uni-DAS 15. Workshop Fahrerassistenz und automatisiertes Fahren, FAS 2023, 24. – 26.10.2023 Kloster Bonlanden, Berkheim. Hrsg.: K. Bengler, 17–26, Uni-DAS
Large-Scale 3D Semantic Reconstruction for Automated Driving Vehicles with Adaptive Truncated Signed Distance Function
Hu, H.; Yang, H.; Wu, J.; Lei, X.; Bieder, F.; Pauls, J.-H.; Stiller, C.
2023. Proc. IEEE Intelligent Vehicles Symposium (IV). Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV55152.2023.10186691
Sensor Data Fusion in Top-View Grid Maps using Evidential Reasoning with Advanced Conflict Resolution
Richter, S.; Bieder, F.; Wirges, S.; Kinzig, C.; Stiller, C.
2022. 25th International Conference on Information Fusion (FUSION), Linköping, Sweden, 04-07 July 2022, Linköping, Sweden, 04-07 July 2022, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/FUSION49751.2022.9841241
TEScalib: Targetless Extrinsic Self-Calibration of LiDAR and Stereo Camera for Automated Driving Vehicles with Uncertainty Analysis
Hu, H.; Han, F.; Bieder, F.; Pauls, J.-H.; Stiller, C.
2022. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6256–6263, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IROS47612.2022.9981651
Interaction-Aware Game-Theoretic Motion Planning for Automated Vehicles using Bi-level Optimization
Burger, C.; Fischer, J.; Bieder, F.; Tas, O. S.; Stiller, C.
2022. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 3978–3985, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC55140.2022.9922600
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding
Peng, K.; Fei, J.; Yang, K.; Roitberg, A.; Zhang, J.; Bieder, F.; Heidenreich, P.; Stiller, C.; Stiefelhagen, R.
2022. IEEE transactions on intelligent transportation systems, 23 (9), 15824–15840. doi:10.1109/TITS.2022.3145588
Improving Lidar-Based Semantic Segmentation of Top-View Grid Maps by Learning Features in Complementary Representations
Bieder, F.; Link, M.; Romanski, S.; Hu, H.; Stiller, C.
2021. Proceedings of 2021 24th International Conference on Information Fusion (FUSION), 64–70, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/FUSION49465.2021.9627069
Fast and Robust Ground Surface Estimation from LiDAR Measurements using Uniform B-Splines
Wirges, S.; Rösch, K.; Bieder, F.; Stiller, C.
2021. 2021 IEEE 24th International Conference on Information Fusion (FUSION). Hrsg.: IEEE, Institute of Electrical and Electronics Engineers (IEEE)
Fusion of Simultaneously Learned Features from Complementary Representations for Semantic Segmentation of Top-View Grid Maps
Bieder, F.; Link, M.; Romanski, S.; Hu, H.; Stiller, C.
2021. Proc. International Conference on Information Fusion (FUSION), IEEEXplore
PillarSegNet: Pillar-based Semantic Grid Map Estimation using Sparse LiDAR Data
Fei, J.; Peng, K.; Heidenreich, P.; Bieder, F.; Stiller, C.
2021. IEEE Intelligent Vehicles Symposium (IV): 11-17 July 2021, online, 838–844, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV48863.2021.9575694
Fusion of sequential LiDAR measurements for semantic segmentation of multi-layer grid maps
Bieder, F.; Wirges, S.; Richter, S.; Stiller, C.
2021. Technisches Messen, 88 (6), 352–360. doi:10.1515/teme-2021-0026
Fusion of Sequential Information for Semantic Grid Map Estimation
Bieder, F.; Rehman, M. U.; Stiller, C.
2020. Forum Bildverarbeitung 2020. Ed.: T. Längle ; M. Heizmann, 79–89, KIT Scientific Publishing
Exploiting Multi-Layer Grid Maps for Surround-View Semantic Segmentation of Sparse LiDAR Data
Bieder, F.; Wirges, S.; Janosovits, J.; Richter, S.; Wang, Z.; Stiller, C.
2020. 2020 IEEE Intelligent Vehicles Symposium (IV), 19 October - 13 November 2020, online, 1892–1898, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IV47402.2020.9304848