Niclas Vödisch

According to our database, Niclas Vödisch authored at least 15 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation.

Niclas Vödisch, Kürsat Petek, Markus Käppeler, Abhinav Valada, Wolfram Burgard

IEEE Robotics Autom. Lett., January, 2025

2024

Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences.

Kürsat Petek, Niclas Vödisch, Johannes Meyer, Daniele Cattaneo, Abhinav Valada, Wolfram Burgard

IEEE Robotics Autom. Lett., November, 2024

Efficient Robot Learning for Perception and Mapping.

Niclas Vödisch

CoRR, 2024

BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation.

Jonas Schramm, Niclas Vödisch, Kürsat Petek, Bangalore Ravi Kiran, Senthil Kumar Yogamani, Wolfram Burgard, Abhinav Valada

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Few-Shot Panoptic Segmentation With Foundation Models.

Markus Käppeler, Kürsat Petek, Niclas Vödisch, Wolfram Burgard, Abhinav Valada

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Collaborative Dynamic 3D Scene Graphs for Automated Driving.

Elias Greve, Martin Büchner, Niclas Vödisch, Wolfram Burgard, Abhinav Valada

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention.

José Arce, Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada

IEEE Robotics Autom. Lett., March, 2023

CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation.

Niclas Vödisch, Kürsat Petek, Wolfram Burgard, Abhinav Valada

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

CoVIO: Online Continual Learning for Visual-Inertial Odometry.

Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization.

Niclas Vödisch, Ozan Unal, Ke Li, Luc Van Gool, Dengxin Dai

IEEE Robotics Autom. Lett., 2022

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning.

Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada

Proceedings of the Robotics Research, 2022

2020

FSOCO: The Formula Student Objects in Context Dataset.

David Dodel, Michael Schötz, Niclas Vödisch

CoRR, 2020

Fast and Accurate Mapping for Autonomous Racing.

Leiv Andresen, Adrian Brandemuehl, Alex Hönger, Benson Kuan, Niclas Vödisch, Hermann Blum, Victor Reijgwart, Lukas Bernreiter, Lukas Schaupp, Jen Jen Chung, Mathias Bürki, Martin R. Oswald, Roland Siegwart, Abel Gawel

CoRR, 2020

Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks.

Andreas Bühler, Niclas Vödisch, Mathias Bürki, Lukas Schaupp

CoRR, 2020

Accurate Mapping and Planning for Autonomous Racing.

Leiv Andresen, Adrian Brandemuehl, Alex Hönger, Benson Kuan, Niclas Vödisch, Hermann Blum, Victor Reijgwart, Lukas Bernreiter, Lukas Schaupp, Jen Jen Chung, Mathias Bürki, Martin R. Oswald, Roland Siegwart, Abel Gawel

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020