Larissa T. Triess

Machine Learning | Autonomous Driving | Computer Vision

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I use machine learning to make autonomous vehicles perceive and understand their environment.

I am a Machine Learning Engineer in the Scene Understanding Group at Mercedes-Benz R&D. As a Product Owner, I am responsible for the Perception, Fusion, and Prediction for the next generation of highly automated vehicles.

Previously, I was a PhD student with the LiDAR Perception Group at Mercedes-Benz R&D and the Karlsruhe Institute of Technology (KIT), where I was advised by Prof. J. Marius Zöllner. My research is published under the title “LiDAR Domain Adaptation - Automotive 3D Scene Understanding”.

news

Jan 2, 2024 Over 100 citations! Within the last year, I reached the magic number of 100 citations on my papers.
Dec 5, 2023 I was appointed member of the advisory board of the Leadership Talent Lab (LTL) at the Karlsruhe Institute of Technology (KIT)
Nov 30, 2023 I held a talk about building an end-to-end differentiable and modular AD stack at the VDI Wissensforum Umfelderfassung im Fahrzeug.
Nov 16, 2023 Yesterday, I held a talk about how to build an autonomous driving stack in the IT-Kolloquium at Esslingen University.
Oct 9, 2023 Last week, I attended ICCV 2023 in Paris, France.

selected publications

  1. A Realism Metric for Generated LiDAR Point Clouds
    Larissa T. Triess, Christoph B. RistDavid Peter, and 1 more author
    International Journal of Computer Vision (IJCV), 2022
  2. Point Cloud Generation with Continuous Conditioning
    Larissa T. Triess, Andre Bühler, David Peter, and 2 more authors
    In Conference on Artificial Intelligence and Statistics (AISTATS), 2022
  3. A Survey on Deep Domain Adaptation for LiDAR Perception
    Larissa T. Triess, Mariella DreissigChristoph B. Rist, and 1 more author
    In Proc. IEEE Intelligent Vehicles Symposium (IV) Workshops, 2021