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

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 7, 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.
May 1, 2021 Our paper on learning cascaded detection tasks with weakly-supervised domain adaptation has been accepted to the IEEE Intelligent Vehicles Symposium 2021!

selected publications

  1. STAR-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations
    Simon DollNiklas HanselmannLukas Schneider, Richard Schulz, Markus Enzweiler, and Hendrik P.A. Lensch
    arXiv 2023
  2. Oral  KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients
    European Conference on Computer Vision (ECCV) 2022
  3. Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation
    Niklas HanselmannNick Schneider, Benedikt Ortelt, and Andreas Geiger
    IEEE Intelligent Vehicles Symposium (IV) 2021