Niclas Vödisch
Albert-Ludwigs-Universität Freiburg |
About me
- 06/2024 - present: Visiting Ph.D. student at the Robotics and Perception Group (University of Zurich) of Prof. Dr. Davide Scaramuzza
- 06/2021 - present: Ph.D. student in the Autonomous Intelligent Systems group of Prof. Dr. Wolfram Burgard; collaborating with the Robot Learning group led by Prof. Dr. Abhinav Valada.
- 09/2018 - 05/2021: M.Sc. in Computational Science and Engineering at ETH Zurich, Switzerland
- 08/2016 - 05/2017: Visiting student at Carnegie Mellon University in Pittsburgh, PA, USA
- 09/2014 - 06/2018: B.Sc. in Computational Engineering Science at RWTH Aachen University, Germany
Research Interests
- Continual Learning for Robotics
- Machine Perception
- Simultaneous Localization and Mapping (SLAM)
Research Projects
Teaching
- Co-organizer, Seminar: Learning with Limited Supervision, SS 2024
- Leading organizer, FreiCAR: Pratical Autonomous Driving, SS 2022, WS 2022/23, WS 2023/24
- TA, Foundations of Deep Learning, WS 2021/22
Students
- Collaborative Scene Graphs, Tim Steinke, Master Thesis, ongoing (with Martin Büchner)
- Label-Efficient LiDAR Panoptic Segmentation With 2D Annoations, Ahmet Canakci, Master Thesis, 09/2024 (with Kürsat Petek)
- Label-Efficient Panoptic Segmentation With Self-Supervised Vision Foundation Models, Markus Käppeler, Master Thesis, 12/2023 (with Kürsat Petek)
- BEVCar: Camera-Radar BEV Object and Semantic Map Segmentation, Jonas Schramm, Master Thesis, 12/2023 (with Kürsat Petek)
- Mapping, Navigation, and Control on a Real-World Autonomous Platform, Tim Steinke, Master Project, 09/2023 (with Martin Büchner)
- COBUS: Collaborative Urban Scene Graph Generation Using Long-Term Panoptic SLAM, Elias Greve, Master Thesis, 07/2023 (with Martin Büchner)
- Cross-Modal Distillation for Multi-Camera 3D Object Detection and BEV Map Segmentation, Markus Käppeler, Master Project, 03/2023 (with Kürsat Petek)
- PADLoC: Deep Loop Closure Detection and Registration Using Panoptic Attention, José Arce y de la Borbolla, Master Thesis, 06/2022 (with Daniele Cattaneo)
Publications
Preprints
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K. Petek*, N. Vödisch*, J. Meyer, D. Cattaneo, A. Valada, and W. Burgard
Automatic Target-Less Camera-LiDAR Calibration from Motion and Deep Point Correspondences
arXiv preprint arXiv:2404.17298, 2024
arXiv Video Website BibTeX -
N. Vödisch*, K. Petek*, M. Käppeler*, A. Valada, and W. Burgard
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation
arXiv preprint arXiv:2405.19035, 2024
arXiv Video Website BibTeX
Workshop Papers
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N. Vödisch, D. Cattaneo, W. Burgard, and A. Valada
CoVIO: Online Continual Learning for Visual-Inertial Odometry
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Vancouver, Canada, 2023
arXiv IEEE Xplore Website BibTeX
Conference Papers
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J. Schramm*, N. Vödisch*, K. Petek*, B R. Kiran, S. Yogamani, W. Burgard, and A. Valada
BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
arXiv preprint arXiv:2403.11761 (accepted for IROS 2024), 2024
arXiv Video Website BibTeX -
M. Käppeler*, K. Petek*, N. Vödisch*, W. Burgard, and A. Valada
Few-Shot Panoptic Segmentation With Foundation Models
IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024
arXiv Website BibTeX -
E. Greve*, M. Büchner*, N. Vödisch*, W. Burgard, and A. Valada
Collaborative Dynamic 3D Scene Graphs for Automated Driving
IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024
arXiv Website BibTeX -
N. Vödisch*, K. Petek*, W. Burgard, and A. Valada
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation
Robotics: Science and Systems (RSS), Daegu, South Korea, 2023
arXiv RSS Video Website BibTex -
N. Vödisch, D. Cattaneo, W. Burgard, and A. Valada
Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning
International Symposium on Robotics Research (ISRR), Geneva, Switzerland, 2022
arXiv Springer Video Website BibTeX -
L. Andresen*, A. Brandemuehl*, A. Hönger*, B. Kuan*, N. Vödisch*, H. Blum, V. Reijgwart, L. Bernreiter, L. Schaupp, J. J. Chung, M. Bürki, M. R. Oswald, R. Siegwart, and A. Gawel
Accurate Mapping and Planning for Autonomous Racing
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA, 2020
arXiv IEEE Xplore Video BibTeX
Journal Papers
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J. Arce, N. Vödisch, D. Cattaneo, W. Burgard, and A. Valada
PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention
IEEE Robotics and Automation Letters (RA-L), vol. 8, issue 3, pp. 1319-1326, March 2023
arXiv IEEE Xplore Video Website BibTex -
N. Vödisch, O. Unal, K. Li, L. Van Gool, and D. Dai
End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization
IEEE Robotics and Automation Letters (RA-L), vol. 7, issue 2, pp. 2242-2249, April 2022
arXiv IEEE Xplore Video Code BibTeX -
N. Vödisch*, D. Dodel*, and M. Schötz*
FSOCO: The Formula Student Objects in Context Dataset
SAE International Journal of Connected and Automated Vehicles, vol. 5, 2022
arXiv SAE Website BibTeX