1 Royden Wagner, Ömer Şahin Taş, Marvin Klemp, Carlos Fernandez, Christoph Stiller
RedMotion: Motion Prediction via Redundancy Reduction, 27.5.2024

2 Kashyap Chitta, Daniel Dauner, Andreas Geiger: SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic, European Conference on Computer Vision (ECCV) 2024 in Milano, Italy, 29.9.2024

3 Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta: NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking, Conference on Neural Information Processing Systems (NeurIPS) 2024, in Vancouver, Canada, 9.12.2024

4 Mohamed-Khalil Bouzidi, Bojan Derajic, Daniel Göhring, Jörg Reichardt: Motion Planning under Uncertainty: Integrating Learning-Based Multi-Modal Predictors into Branch Model Predictive Control, IEEE International Conference on Intelligent Transportation Systems, Edmonton, Canada, 24.-27.9.2024

5 Nick Stracke, Stefan Andreas Baumann, Josh Susskind, Miguel Angel Bautista, Björn Ommer: CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models, ECCV, Milan, 29.9.-4.10.2024

6 Vincent Tao Hu, Stefan Andreas Baumann, Ming Gui, Olga Grebenkova, Pingchuan Ma, Johannes Fischer, Björn Ommer: ZigMa: A DiT-style Zigzag Mamba Diffusion Model, ECCV, Milan, 29.9.-4.10.2024

7 Joannes S Fischer, Ming Gui, Pingchuan Ma, Nick Stracke, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer: FMBoost: Boosting Latent Diffusion with Flow Matching, ECCV, Milan, 29.9.-4.10.2024

8 Omer Sahin Tas, Royden Wagner: Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers,  Conference on Neural Information Processing Systems (NeurIPS) 2024,Vancouver, Canada, 9.12.2024

9 Royden Wagner, Ömer Şahin Taş, Marvin Klemp, Carlos Fernandez: JointMotion: Joint Self-Supervision for Joint Motion Prediction, Conference on Robot Learning (CoRL), Munich, 6.11.24

10 Kumar Manas, Stefan Zwicklbauer, Adrian Paschke: CoT-TL: Low-Resource Temporal Knowledge Representation of Planning Instructions using Chain-of-Thought Reasoning, IEEE/RSJ International Conference on Intelligent Robots and Systems, Abu Dhabhi, 14.10.24

11 Dmytro Kotovenko, Olga Grebenkova, Nikolaos Sarafianos, Avinash Paliwal, Pingchuan Ma, Omit Poursaeed, Sreyas Mohan, Yuchen Fan, Yilei Li, Rakesh Ranjan, Björn Ommer: WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussians, ECCV, Milan, 29.9.-4.10.2024

12 Marius Kästingschäfer, Théo Gieruc, Sebastian Bernhard, Dylan Campbell, Eldar Insafutdinov, Eyvaz Najafli, Thomas Brox: SEED4D: A Synthetic Ego–Exo Dynamic 4D Data Generator, Driving Dataset and Benchmark, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2025), Tucson, Arizona, 28.2.2025

13 Laurenz Adolph, Barbara Schütt, David Kraus, Eric Sax: Navigating Dimensionality Through State Machines in Automotive System Validation, MODELSWARD 2025, Porto, Portugal, 26.2.25

14 Natalie Grabowsky, Annika Mütze, Joshua Wendland, Nils Jansen, Matthias Rottmann: Does Knowledge About Perceptual Uncertainty Help an Agent in Automated Driving?, IEEE Intelligent Vehicles Symposium, Cluj-Napoca, Romania, 22-25.6.25

15 Franz Andert, Oliver Böttcher, Aditya Mushyam, Philipp Schmälzle: Semantic LiDAR Point Cloud Mapping and Cloud-Based SLAM for Autonomous Driving, IEEE/ION PLANS 2025 Salt Lake Downtown City Creek, UT, USA, 28.4.-1.5.2025

16 Ming Gui, Johannes Schusterbauer, Ulrich Prestel, Pingchuan Ma, Dmytro Kotovenko, Olga Grebenkova, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer: DepthFM: Fast Generative Monocular Depth Estimation with Flow Matching, AAAI Conference on Artificial Intelligence, Philadelphia, USA, 27.2.-4.3.2025

17 Pingchuan Ma, Lennart Rietdorf, Dmytro Kotovenko, Vincent Tao Hu, Björn Ommer: Does VLM Classification Benefit from LLM Description Semantics?  AAAI Conference on Artificial Intelligence, Philadelphia, USA, 27.2.-4.3.2025

18 Dominik Grundt, Astrid Rakow, Philipp Borchers, Eike Möhlmann: What does AI Need to Know to Drive: Testing Relevance of Knowledge, Science of Computer Programming

19 Katharina Winter, Mark Azer, Fabian Flohr: BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving, IEEE, 5.5.2025

20 Katharina Winter, Abhishek Vivekanandan, Rupert Polley, Yinzhe Shen, Christian Schlauch, Mohamed-Khalil Bouzidi, Bojan Derajic, Natalie Grabowsky, Annajoyce Mariani, Dennis Rochau, Giovanni Lucente, Harsh Yadav, Firas Mualla, Adam Molin, Sebastian Bernhard, Christian Wirth, Ömer Sahin Tas, Nadja Klein, Fabian Flohr, Hanno Gottschalk: Generative AI for Autonomous Driving: A Review, IEEE, 5.5.2025

21 Shuxiao Ding, Yutong Yang, Julian Wiederer, Markus Braun, Peizheng Li, Juergen Gall, Bin Yang: TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking, 4.4.2025