collaborators

5 papers

cs.RO2025

ParkDiffusion: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction for Automated Parking using Diffusion Models

Jiarong Wei, Niclas Vödisch, Anna Rehr +2

Automated parking is a critical feature of Advanced Driver Assistance Systems (ADAS), where accurate trajectory prediction is essential to bridge perception and planning modules. D…

cs.CV2025

Label-Efficient LiDAR Panoptic Segmentation

Ahmet Selim Çanakçı, Niclas Vödisch, Kürsat Petek +2

A main bottleneck of learning-based robotic scene understanding methods is the heavy reliance on extensive annotated training data, which often limits their generalization ability.…

cs.RO2025

Collaborative Dynamic 3D Scene Graphs for Open-Vocabulary Urban Scene Understanding

Tim Steinke, Martin Büchner, Niclas Vödisch +1

Mapping and scene representation are fundamental to reliable planning and navigation in mobile robots. While purely geometric maps using voxel grids allow for general navigation, o…

cs.RO2024

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

Niclas Vödisch, Kürsat Petek, Markus Käppeler +2

A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achie…

cs.RO2024

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

Kürsat Petek, Niclas Vödisch, Johannes Meyer +3

Sensor setups of robotic platforms commonly include both camera and LiDAR as they provide complementary information. However, fusing these two modalities typically requires a highl…