Datasets › H3D

H3D (Honda Research Institute 3D)

Introduced by Abhishek Patil et al. in The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes archive 2025-07-28

The H3D is a large scale full-surround 3D multi-object detection and tracking dataset. It is gathered from HDD dataset, a large scale naturalistic driving dataset collected in San Francisco Bay Area. H3D consists of following features:

  • Full 360 degree LiDAR dataset (dense pointcloud from Velodyne-64)
  • 160 crowded and highly interactive traffic scenes
  • 1,071,302 3D bounding box labels
  • 8 common classes of traffic participants (Manually annotated every 2Hz and linearly propagated for 10 Hz data)
  • Benchmarked on state-of-the art algorithms for 3D only detection and tracking algorithms.

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 39 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Custom

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • H3D

1 variant name, as the archive lists them.

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