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; et al. (IROS, 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)

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; et al. (CoRR, 2020)

FSOCO: The Formula Student Objects in Context Dataset. - David Dodel; Michael Schötz; Niclas Vödisch (CoRR, 2020)

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning. - Niclas Vödisch; Daniele Cattaneo 001; Wolfram Burgard; Abhinav Valada (ISRR, 2022)

End-to-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization. - Niclas Vödisch; Ozan Unal; Ke Li 021; Luc Van Gool; Dengxin Dai (IEEE Robotics Autom. Lett., 2022)

CoVIO: Online Continual Learning for Visual-Inertial Odometry. - Niclas Vödisch; Daniele Cattaneo 001; Wolfram Burgard; Abhinav Valada (CVPR Workshops, 2023)

CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation. - Niclas Vödisch; Kürsat Petek; Wolfram Burgard; Abhinav Valada (Robotics: Science and Systems, 2023)

PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention. - José Arce; Niclas Vödisch; Daniele Cattaneo 001; Wolfram Burgard; Abhinav Valada (IEEE Robotics Autom. Lett., 2023)

Collaborative Dynamic 3D Scene Graphs for Automated Driving. - Elias Greve; Martin Büchner; Niclas Vödisch; Wolfram Burgard; Abhinav Valada (ICRA, 2024)

Few-Shot Panoptic Segmentation With Foundation Models. - Markus Käppeler; Kürsat Petek; Niclas Vödisch; Wolfram Burgard; Abhinav Valada (ICRA, 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 (IROS, 2024)

Efficient Robot Learning for Perception and Mapping. - Niclas Vödisch (CoRR, 2024)

Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences. - Kürsat Petek; Niclas Vödisch; Johannes Meyer; Daniele Cattaneo 001; Abhinav Valada; Wolfram Burgard (IEEE Robotics Autom. Lett., 2024)

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., 2025)

LiDAR Registration with Visual Foundation Models. - Niclas Vödisch; Giovanni Cioffi; Marco Cannici; Wolfram Burgard; Davide Scaramuzza 001 (CoRR, 2025)

Label-Efficient LiDAR Panoptic Segmentation. - Ahmet Selim Çanakçi; Niclas Vödisch; Kürsat Petek; Wolfram Burgard; Abhinav Valada (CoRR, 2025)

Collaborative Dynamic 3D Scene Graphs for Open-Vocabulary Urban Scene Understanding. - Tim Steinke; Martin Büchner; Niclas Vödisch; Abhinav Valada (CoRR, 2025)

ParkDiffusion: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction for Automated Parking using Diffusion Models. - Jiarong Wei; Niclas Vödisch; Anna Rehr; Christian Feist; Abhinav Valada (CoRR, 2025)