Niklas Hanselmann

PhD student | machine learning, vision and robotics

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I am a PhD student with the Scene Understanding Group at Mercedes-Benz R&D, as well as the University of Tübingen and the Max Planck Institute for Intelligent Systems, where I am advised by Prof. Andreas Geiger.

Previously I was a master’s student at the Karlsruhe Institute of Technology, where I completed my master’s thesis at the Department of Measurement and Control, supervised by Prof. Christoph Stiller.

My research interests lie at the intersection of machine learning, robotics and computer vision. In particular, I am interested in learning robust representations for perception and planning from simulation.

news

Jun 30, 2024 STAR-Track, our RA-L paper on latent motion models has been selected for oral presentation at IROS this year!
Jul 15, 2022 I will be presenting KING at the ICML 2022 Workshop on Safe Learning for Autonomous Driving (SL4AD) next week. If you’re around, come say hi!
Jul 07, 2022 KING, our paper on gradient-based generation of safety-critical driving scenarios, has been accepted to this year’s European Conference on Computer Vision (ECCV) as an oral.

selected publications

  1. emperror_dynamic_teaser.webp
    EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners
    arXiv, 2024
  2. dualad_teaser.webp
    DualAD: Disentangling the Dynamic and Static World for End-to-End Driving
    Simon DollNiklas HanselmannLukas Schneider, Richard Schulz, Marius CordtsMarkus Enzweiler, and Hendrik P.A. Lensch
    Conference on Computer Vision and Pattern Recognition (CVPR), 2024
  3. king_animated_thumbnail.gif
    Oral   KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients
    European Conference on Computer Vision (ECCV), 2022