Datasets › DDAD
DDAD (Dense Depth for Autonomous Driving)
DDAD is a new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions. It contains monocular videos and accurate ground-truth depth (across a full 360 degree field of view) generated from high-density LiDARs mounted on a fleet of self-driving cars operating in a cross-continental setting. DDAD contains scenes from urban settings in the United States (San Francisco, Bay Area, Cambridge, Detroit, Ann Arbor) and Japan (Tokyo, Odaiba).
Source: https://github.com/TRI-ML/DDAD Image Source: https://github.com/TRI-ML/DDAD
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Monocular Depth Estimation | DDAD | AFNet RMSE 4.60 | Adaptive Fusion of Single-View and Multi-View Depth for... | junda24/afnet | 4 | Compare |
Papers archive 2025-07-28
4 shown of 4 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 73. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation | 1 | 1 | 11 Jul 2024 | not harvested |
| Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving | 1 | 1 | 12 Mar 2024 | ran 7 of 8 samples (1 unverified) |
| GEDepth: Ground Embedding for Monocular Depth Estimation | 2 | 1 | 18 Sep 2023 | not harvested |
| TransDSSL: Transformer based Depth Estimation via Self-Supervised Learning | 1 | 1 | 5 Aug 2022 | not harvested |
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
- DDAD
1 variant name, as the archive lists them.
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