Maximilian Denninger
Maximilian Denninger
Deep Learning Engineer at Apple
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Cited by
Cited by
M Denninger, M Sundermeyer, D Winkelbauer, Y Zidan, D Olefir, ...
arXiv preprint arXiv:1911.01911, 2019
BlenderProc: Reducing the Reality Gap with Photorealistic Rendering
M Denninger, M Sundermeyer, D Winkelbauer, D Olefir, T Hodan, Y Zidan, ...
Robotics: Science and Systems (RSS) Workshops, 2020
3D Scene Reconstruction from a Single Viewport
M Denninger, R Triebel
Proceedings of the European Conference on Computer Vision (ECCV), 2020
An Ecosystem for Heterogeneous Robotic Assistants in Caregiving: Core Functionalities and Use Cases
J Vogel, D Leidner, A Hagengruber, M Panzirsch, B Bauml, M Denninger, ...
IEEE Robotics & Automation Magazine 28 (3), 12-28, 2020
Persistent Anytime Learning of Objects from Unseen Classes
M Denninger, R Triebel
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018
Learning to Localize in New Environments from Synthetic Training Data
D Winkelbauer, M Denninger, R Triebel
2021 IEEE International Conference on Robotics and Automation (ICRA), 5840-5846, 2021
Monte Carlo registration and its application with autonomous robots
C Rink, S Kriegel, D Seth, M Denninger, ZC Marton, T Bodenmüller
Journal of Sensors 2016, 2016
Introduction to Surface Avatar: the First Heterogeneous Robotic Team to be Commanded with Scalable Autonomy from the ISS
NYS Lii, P Schmaus, D Leidner, T Krueger, J Grenouilleau, A Pereira, ...
Proceedings of the International Astronautical Congress, IAC, 2022
RECALL: Rehearsal-free Continual Learning for Object Classification
M Knauer, M Denninger, R Triebel
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
HOWS-CL-25: Household Objects Within Simulation Dataset for Continual Learning
MW Knauer, M Denninger, R Triebel
Zenodo. org, 2022
An efficient probabilistic online classification approach for object recognition with random forests
M Denninger
Technische Universität München, 2017
An exemplary application of decision theory in robotics: autonomous calibration of depth cameras with non-overlapping fields of view on a mobile platform
M Denninger
University of Applied Science Kempten, 2015
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