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Maximilian Denninger

DLR German Aerospace Center
Institute of Robotics and Mechatronics
Perception and Cognition
Muenchener Str. 20
82234 Wessling

telephone: +49 8153 28-3240
email: Maximilian Denninger

I started at the DLR in 2014 as a student and have done my bachelor thesis and my master thesis there. Nowadays, I am doing my PhD in the field of machine learning with a focus on 3D reconstruction of scenes.


With my colleague Martin Sundermeyer am I working on our internal Open Source Solution named BlenderProc. This software is able to help with the process of data generation for the training of neural networks, as we believe this is one of the major challenges of modern machine learning.



  • Maximilian Denninger, Rudolph Triebel:
    3D Scene Reconstruction from a Single Viewport
    In: 16th European Conference on Computer Vision, ECCV 2020, European Conference on Computer Vision, vol. 16. European Conference on Computer Vision ECCV 2020, 23.-28. August 2020, Virtuell, 2020. DOI 10.1007/978-3-030-58542-6_4, ISBN 978-3-030-58541-9. [elib]
  • Maximilian Denninger, Martin Sundermeyer, Dominik Winkelbauer, Dmitry Olefir, Tomas Hodan et 5 al.:
    BlenderProc: Reducing the Reality Gap with Photorealistic Rendering
    In: International Conference on Robotics: Sciene and Systems, RSS 2020. Robotics: Science and Systems (RSS), 12.-16. Juli 2020, Virtuell, 2020. [elib]
  • Jörn Vogel, Daniel Leidner, Annette Hagengruber, Michael Panzirsch, Berthold Bäuml et 11 al.:
    An Ecosystem for Heterogeneous Robotic Assistants in Caregiving
    IEEE Robotics & Automation Magazine. IEEE - Institute of Electrical and Electronics Engineers, 2020. DOI 10.1109/MRA.2020.3032142, ISSN 1070-9932. [elib]
  • Maximilian Denninger, Rudolph Triebel:
    Persistent Anytime Learning of Objects from Unseen Classes
    In: IEEE International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), 01 Oct - 05 Oct 2018, Madrid, Spain, 2018. [elib]
  • Maximilian Denninger:
    An efficient probabilistic online classification approach for object recognition with random forests
    Master's. Technische Universität München, 2017. [elib]
  • Christian Rink, Simon Kriegel, Daniel Seth, Maximilian Denninger, Zoltan-Csaba Marton et 1 al.:
    Monte Carlo Registration and Its Application with Autonomous Robots
    Journal of Sensors, vol. 2016. Hindawi Publishing Corporation, 2016. DOI 10.1155/2016/2546819, ISSN 1687-725X. [elib]
  • Maximilian Denninger:
    An exemplary application of decision theory in robotics: autonomous calibration of depth cameras with non-overlapping fields of view on a mobile platform
    Bachelor's. Hochschule Kempten, 2015. [elib]


Last updated on Monday, 21 June 2021 by Maximilian Denninger