Veröffentlichungen: KI Data Tooling

Nachstehend werden wissenschaftliche Beiträge und Veröffentlichungen aus dem Projekt KI Data Tooling aufgeführt.

Konrad Doll: „KI Data Tooling“: Werkzeugkasten für die künstliche Intelligenz im Automobil. In: Sensorik Magazin, Ausgabe 102, 07/2020.
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”.
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.
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.
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.
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.
Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick: Smart Infrastructure: A research junction. In: 7th IEEE International Smart Cities Conference 2021.
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.
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.
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.
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".
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.
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.
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.
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.
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.
Jasmin Breitenstein, Tim Fingscheidt: Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge Baseline . In: IV2022, 06.-08.06.2022.
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.
Daniel Bogdoll, Maximilian Nitsche, J. Marius Zöllner: Anomaly Detection in Autonomous Driving: A Survey. In: CVPR 2022 Workshop on Autonomous Driving, 20.06.2022.
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.
Jan Schneegans, Maarten Bieshaar, Bernhard Sick: A Practical Evaluation of Active Learning Approaches for Object Detection.
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.
Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk: Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects In: Asian Conference on Computer Vision (ACCV2022) in Macau SAR, China, 04-08.12.2022
Daniel Bogdoll: One Ontology to Rule Them All: Corner Case Scenarios for Autonomous Driving In:ECCV-SAIAD 2022, Tel Aviv -Yafo, Israel, 23.10.2022
Kamil Kowol, Prof. Stefan Bracke, Prof. Hanno Gottschalk: A-Eye: Driving with the Eyes of AI for Corner Case Generation In: International Conference on Computer-Human Interaction Research and Applications (CHIRA) in Valletta, Malta, 27.-28.10.2022
Jasmin Breitenstein, Jonas Löhdefink, Tim Fingscheidt: Joint Prediction of Amodal and Visible Semantic Segmentation for Automated Driving In: ECCV-AVVision 2022 , Tel Aviv -Yafo, Israel, 23.10.2022
Philipp Rigoll, Lennart Ries, Eric Sax: Scalable Data Set Distillation for the Development of Automated Driving Functions , ITSC 2022, Macau China, 18.9.-12.10.2022
Maximilian Menke, Thomas Wenzel, Andreas Schwung: AWADA: Foreground-Focused Adversarial Learning for Cross-Domain Object Detection, Computer Vision and Image Understanding
Daniel Bogdoll, Svenja Uhlemeyer, Kamil Kowol: Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey , IV 2023, USA, 04.06.2023
Maximilian Menke, Thomas Wenzel, Andreas Schwung: Improving Cross-Domain Semi-Supervised Object Detection with Adversarial Domain Adaptation , Intelligent Vehicle Symposium, Anchorage, Alaska, USA, 04.-07.06.2023
Marvin Klemp, Kevin Rösch , Royden Wagner, Martin Lauer: LDFA: Latent Diffusion Face Anonymization for Self-driving Applications , CVPR Vancover, 18.06.2023
Hannes Reichert, Manuel Hetzel, Steven Schreck, Konrad Doll, Bernhard Sick: Sensor Equivariance by LiDAR Projection Image , Anchorage Alaska, 04.06.2023
Manuel Hetzel, Hannes Reichert, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick: The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset , Anchorage Alaska, 04.06.2023
Kamil Kowol, Stefan Bracke, Hanno Gottschalk: survAIval: Survival Analysis with the Eyes of AI , Communications in Computer and Information Science (CCIS), Springer
Philipp Rigoll, Patrick Petersen, Hanno Stage, Lennart Ries, Eric Sax: Focus on the Challenges: Analysis of a User-friendly Data Search Approach with CLIP in the Automotive Domain , ITSC 2023, Bilbao Spain, 24.-28.09.2023
Isabelle Tülleners, Tobias Moers, Thomas Schulik, Martin Sedlacek: A Semi-Automated Corner Case Detection and Evaluation Pipeline , 25.05.2023
Rupert Polley: Un- and Supervised Inpainting for Aerial Image Segmentation, ITSC 2023, Bilbao Spain, 24.09.2023
Aditya Kumar Agarwal: Modelling of Epistemic Uncertainty for Active Learning in Deep Detection Neural Network, British Machine Vision Conference 2023, Aberdeen, UK, 20. -24.11.2023
Clemens Schicktanz, Lars Klitzke, Kay Gimm: Microscopic Analysis of the Impact of Congestion on Traffic Safety and Efficiency at a Signalized Intersection: A Case Study, ITSC 2023, Bilbao Spain, 24.09.2023