Monte Carlo Registration and Its Application with Autonomous Robots. - Christian Rink; Simon Kriegel; Daniel Seth; Maximilian Denninger; Zoltan-Csaba Marton; Tim Bodenmüller (J. Sensors, 2016)

Persistent Anytime Learning of Objects from Unseen Classes. - Maximilian Denninger; Rudolph Triebel (IROS, 2018)

BlenderProc. - Maximilian Denninger; Martin Sundermeyer; Dominik Winkelbauer; Youssef Zidan; Dmitry Olefir; Mohamad Elbadrawy; Ahsan Lodhi; Harinandan Katam (CoRR, 2019)

3D Scene Reconstruction from a Single Viewport. - Maximilian Denninger; Rudolph Triebel (ECCV (22), 2020)

Learning to Localize in New Environments from Synthetic Training Data. - Dominik Winkelbauer; Maximilian Denninger; Rudolph Triebel (ICRA, 2021)

An Ecosystem for Heterogeneous Robotic Assistants in Caregiving: Core Functionalities and Use Cases. - Jörn Vogel; Daniel Leidner; Annette Hagengruber; Michael Panzirsch; Berthold Bäuml; Maximilian Denninger; Ulrich Hillenbrand; Lioba Suchenwirth; Peter Schmaus; Marco Sewtz; Adrian Simon Bauer; Thomas Hulin; et al. (IEEE Robotics Autom. Mag., 2021)

RECALL: Rehearsal-free Continual Learning for Object Classification. - Markus Knauer; Maximilian Denninger; Rudolph Triebel (IROS, 2022)

3D Semantic Scene Reconstruction from a Single Viewport. - Maximilian Denninger; Rudolph Triebel (IMPROVE, 2023)

Persistent Learning for Semantic Indoor Mapping in Dynamic Environments. - Maximilian Denninger (2023)

BlenderProc2: A Procedural Pipeline for Photorealistic Rendering. - Maximilian Denninger; Dominik Winkelbauer; Martin Sundermeyer; Wout Boerdijk; Markus Knauer; Klaus H. Strobl; Matthias Humt; Rudolph Triebel (J. Open Source Softw., 2023)