The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset
Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity. We present KITScenes Multimodal, a European dataset built around high-fidelity sensors and maps. Our fully synchronized sensor suite combines high-resolution global-shutter cameras, long-range lidar beyond 400m, 4D imaging radar, and redundant GNSS/INS localization. Our HD maps are, to our knowledge, the most complete of any sensor dataset, validated through autonomous driving trials on open-source software. For the first time in a public dataset, all driving-relevant traffic elements, such as traffic lights, are mapped in 3D to a reprojection-acc...
| Authors | Richard Schwarzkopf, Fabian Immel, Alexander Blumberg et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 June 2026 |
| Last updated at source | 1 June 2026 |
Connected in the knowledge graph
- Voxel51/kitscenes-multimodalDataset · cited by
- KIT-MRT/KITScenes-MultimodalDataset · cited by
Models and datasets referencing this paper
- KIT-MRT/KITScenes-MultimodalDataset
- Voxel51/kitscenes-multimodalDataset
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