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 | 105 | 2020 |
Blenderproc2: A procedural pipeline for photorealistic rendering M Denninger, D Winkelbauer, M Sundermeyer, W Boerdijk, MW Knauer, ... Journal of Open Source Software 8 (82), 4901, 2023 | 77 | 2023 |
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 | 2 | 2022 |
Hows-cl-25: Household objects within simulation dataset for continual learning MW Knauer, M Denninger, R Triebel Zenodo. org, 2022 | 1 | 2022 |
Interactive incremental learning of generalizable skills with local trajectory modulation M Knauer, A Albu-Schäffer, F Stulp, J Silvério arXiv preprint arXiv:2409.05655, 2024 | | 2024 |
Grounding Embodied Question-Answering with State Summaries from Existing Robot Modules S Bustamante Gomez, MW Knauer, T Jeremias, S Schneyer, B Weber, ... RSS (Robotics: Science and Systems) conference 2024, Generative Modeling …, 2024 | | 2024 |
A persistent incremental learning approach for object classification of unseen categories using convolutional neural networks on mobile robots M Knauer Hochschule Kempten, 2020 | | 2020 |
Intuitive Instruction of Robot Systems: Semantic Integration of Standardized Skill Interfaces J Ding, I Kessler, A Perzylo, M Knauer, A Dömel, C Willibald, S Riedel, ... | | |
Grounding Embodied Question-Answering with State Summaries from Existing Robot Modules S Bustamante, M Knauer, J Thun, S Schneyer, B Weber, F Stulp | | |