Scientific contributions and publications from KI Data Tooling are listed below:

  1. Konrad Doll: „KI Data Tooling“: Werkzeugkasten für die künstliche Intelligenz im Automobil. In: Sensorik Magazin, Ausgabe 102, 07/2020.
  2. Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick: Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders. In: arXiv preprint for SAIAD 2021 Workshop “Safe Artificial Intelligence for Automated Driving”.
  3. Jan Schneegans, Maarten Bieshaar, Florian Heidecker, Bernhard Sick: Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. In: Pattern Recognition. ICPR International Workshops and Challenges, Virtual Event, 10.-15.01.2021.
  4. Jan Schneegans, Jan Eilbrecht, Stefan Zernetsch, Maarten Bieshaar, Konrad Doll, Olaf Stursberg, Bernhard Sick: Probabilistic VRU Trajectory Forecasting for Model-Predictive PlanningA Case Study: Overtaking Cyclists. In: IEEE IV 2021.
  5. Florian Heidecker, Abdul Hannan, Maarten Bieshaar, Bernhard Sick: Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. In: ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges.
  6. Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, and Bernhard Sick: An  Application-Driven  Conceptualization  of  Corner  Casesfor  Perception  in  Highly  Automated  Driving. In: 32nd IEEE Intelligent Vehicles Symposium.
  7. Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick: Smart Infrastructure: A research junction. In: 7th IEEE International Smart Cities Conference 2021.
  8. Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner: Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. In: 7t IEEE International Smart Cities Conference 2021.
  9. Maarten Bieshaar, Stefan Zernetsch, Katharina Riepe, Konrad Doll, Bernhard Sick: Cyclist Motion State Forecasting – Going beyond Detection. In: 24th IEEE International Conference on Intelligent Transportation Systems - ITSC2021, Indianapolis.
  10. Maarten Bieshaar, Marek Herde, Denis Huselijc, Bernhard Sick: A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. In: 5th International Workshop on Interactive Adaptive Learning 2021.
  11. Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner: Description of Corner Cases in Automated Driving: Goals and Challenges. In: ICCV 2021 Workshop on "Embedded and Real-World Computer Vision in Autonomous Driving".
  12. Philipp Rigoll, Patrick Petersen, Jacob Langner, Eric Sax: Parameterizable lidar-assisted traffic sign placement for the augmentation of driving situations with CycleGAN. In: ICSEng 2021: International Conference On Systems Engineering.
  13. Dominik Salles Lukas Lang Martin Kehrer et al.: A Modular Co-Simulation Framework with Open Source Software and Automotive Standards. In: 22. Internationales Stuttgarter Symposium, 15.-16.03.2022.
  14. Philipp Rigoll, Patrick Petersen, Lennart Ries, Jacob Langner und Eric Sax: Augmentation of camera data via Generative Adversarial Networks (GANs) for the validation of automated driving functions. In: 35. VDI Tagung: Fahrerassistenzsysteme und Automatisiertes Fahren, 17.-18.05.2022.
  15. Kamil Kowol, Stefan Bracke, Hanno Gottschalk: A-Eye: Driving with the Eyes of AI for Corner Case Generation. In: 33rd IEEE Intelligent Vehicles Symposium in Aachen, 05.-09.06.2022.
  16. Jonas Löhdefink, Jonas Sitzmann, Andreas Bär, Tim Fingscheidt: Adaptive Bitrate Quantization Scheme Without Codebook for Learned Image Compression. In: CVPR - Workshop, Challenge on Learned Image Compression (CLIC), New Orleans, 19.06.2022.
  17. Jasmin Breitenstein, Tim Fingscheidt: Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge Baseline. In: IV2022, 06.-08.06.2022.
  18. Stefan Zernetsch, Hannes Reichert, Viktor Kreß, Konrad Doll, Bernhard Sick: A Holistic View on Probabilistic Trajectory Forecasting – Case Study: Cyclist Intention Detection. In: IV2022, 06.-08.06.2022.
  19. Daniel Bogdoll, Maximilian Nitsche, J. Marius Zöllner: Anomaly Detection in Autonomous Driving: A Survey. In: CVPR 2022 Workshop on Autonomous Driving, 20.06.2022.
  20. Claudia Drygala, Matthias Rottmann, Hanno Gottschalk: Closing the Domain Gap between Synthetic and Real-world Data for Semantic Segmentation by cGAN. In: Robust Understanding of Street Scenes Using Computer Vision, Zagreb, 22.-23.09.2022.
  21. Jan Schneegans, Maarten Bieshaar, Bernhard Sick: A Practical Evaluation of Active Learning Approaches for Object Detection.
  22. Lukas Lang, Kmeid Saad, Dominik Salles: Automotive Radar Antenna Configurations and their Impact on Machine Learning Approaches: A Case Study. In: Driving Simulation Converence (DSC22), Straßburg, 14.-16.09.2022.



Here the public KI Data Tooling presentations are listed.



Dr. Hans-Jörg Vögel: KI Data Tooling: Hochautomatisierte Entwicklung datengetriebener Funktionen.

Joint event of the Federal Ministry for Economic Affairs and Energy and the VDA. 02.03.2021.(pdf:3 MB)

Günther Hasna: Real-time Automotive Radar Simulation for Busy Intersection Autonomous Driving Scenarios.

VDI-Tagung Fahrerassistenzsysteme und Automatisiertes Fahren, 17./18.05.2022. (pdf:4 MB)

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