Olaf Dünkel

I am a second-year Ph.D. student at the Max Planck Institute for Informatics and Saarland University advised by Dr. Adam Kortylewski and Prof. Dr. Christian Theobalt. I am part of ELLIS, co-advised by Prof. Christian Rupprecht (VGG, University of Oxford).

My research interests lie at the intersection of computer vision and generative models: My goal is to leverage the power of generative models to improve the robustness and generalization of computer vision systems. Other than that, I keep being excited about autonomous driving and robotics.

Prior to my PhD, I interned at Porsche and VITA (EPFL), working on autonomous driving, and I pursued my master thesis at KIT, advised by F. Pfaff and T. Salzmann. I obtained my Bachelor's in EECS and my Master's in Signal Processing and Robotics from KIT.

Email  /  Scholar  /  LinkedIn  /  Bluesky  /  GitHub

profile photo

Updates

  • Feburary 2025: Our work "Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature Space" was accepted to CVPR 2025.
  • July 2024: Invited talk at the 3rd Virtual Symposium on Directional Statistics.
  • Feburary 2024: The paper from my master thesis HuProSO3 was accepted to CVPR 2024.
  • November 2023: I started my PhD as an ELLIS student at the Max Planck Institute for Informatics

Research

I'm interested in generative models and computer vision. Specifically, I am working on generative benchmarking and on leveraging the knowledge contained in generative models to better solve challenging vision tasks. Previously, I worked on autonomous driving and vehicle trajectory prediction.

Normalizing Flows Normalizing Flows on the Product Space of SO(3) Manifolds for Probabilistic Human Pose Modeling
O. Dünkel, T. Salzmann, F. Pfaff
CVPR, 2024.
paper / GitHub
Joint Vehicle Trajectory Joint Vehicle Trajectory and Cut-In Prediction on Highways using Output Constrained Neural Networks
M. Brosowsky, P. Orschau, O. Dünkel, P. Elspas, D. Slieter, M. Zöllner
IEEE Symposium Series on Computational Intelligence, 2021.
paper
Output Constraints Sample-Specific Output Constraints for Neural Networks
M. Brosowsky, F. Keck, O. Dünkel, M. Zöllner
AAAI, 2021.
paper

Recent Positions

  • July 2022 - October 2022:
    Research Internship Vehicle Trajectory Prediction at VITA (EPFL)
  • November 2019 - April 2020:
    Bachelor's Thesis on Uncertainty Estimation in Vehicle Trajetory Prediction at Porsche AG
  • April 2019 - August 2019:
    Intern for Autonomous Driving and Deep Learning at Porsche AG

Miscellaneous

I am a passionate French horn player and I am regularly playing in various symphony orchestras. Music not only brought me to various places across the world but it keeps being a great regular joy of my life.
Other than that I do like sports, especially long distance running, swimming, hiking, and volleyball.

This website is based on Jon Barron's website, whose code is available on Jon Barron's GitHub page.