Datasets › SemanticSpray Dataset

SemanticSpray Dataset

1 Jul 2023 archive 2025-07-28

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LiDARs are one of the main sensors used for autonomous driving applications, providing accurate depth estimation regardless of lighting conditions. However, they are severely affected by adverse weather conditions such as rain, snow, and fog.

This dataset provides semantic labels for a subset of the Road Spray dataset, which contains scenes of vehicles traveling at different speeds on wet surfaces, creating a trailing spray effect. We provide semantic labels for over 200 dynamic scenes, labeling each point in the LiDAR point clouds as background (road, vegetation, buildings, ...), foreground (moving vehicles), and noise (spray, LiDAR artifacts).

The SemanticSpray dataset contains scenes in wet surface conditions captured by Camera, LiDAR, and Radar.

The following label types are provided:

  • Camera: 2D Boxes

  • LiDAR: 3D Boxes, Semantic Labels

  • Radar: Semantic Labels

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • SemanticSpray Dataset

1 variant name, as the archive lists them.

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