| --- |
| gated: manual |
| license: other |
| license_name: co3dv2-source-license |
| license_link: https://github.com/facebookresearch/co3d |
| tags: |
| - co3d |
| - multi-view |
| - depth |
| - processed |
| --- |
| # CO3Dv2 indexed training data |
|
|
| **Upload in progress.** Consult `dataset-status.json` for completion and coverage. |
| The target is every annotated frame in all 51 categories of the official |
| `co3dv2_231130` release. Partial uploads must not be interpreted as the full dataset. |
|
|
| Each `all/<category>/part-NNNN/` prefix is directly readable with `HFByteSource` |
| and `SceneIndex`. Each part has HDF5 payloads, NPZ indices, verified completion |
| records, a packing plan, and a manifest published only after artifact verification. |
| The final `catalog.json` lists every part only after all categories are complete. |
|
|
| RGB is resized without upsampling to a maximum height of 480 (even dimensions), |
| encoded with H.264 CRF 18 and closed GOP 8. Cameras use OpenCV c2w and normalized |
| intrinsics. Depth is float16 with a validity mask and Zstandard compression; |
| depth and camera translations retain CO3D reconstruction units, **not guaranteed |
| metres**. These are lossy training derivatives. |
|
|
| The `all` selection preserves all annotated frames, labels every frame as a |
| training view, and **does not implement an official benchmark train/val/test |
| protocol**. Original official split lists are retained in `provenance/`. |
| Foreground probability masks, point clouds, and optical flow are not packed. |
|
|
| Source: [Meta's CO3D release](https://github.com/facebookresearch/co3d). |
| Original source archives are downloaded and verified against the official SHA-256 |
| list. Source archive hashes, original split metadata, category licenses, converter |
| revision, and per-scene selected asset digests accompany the derivatives. |
| See each category's original license under `provenance/`. Changes are the |
| conversion, resizing, video/depth encoding, and camera convention conversion above. |
|
|
| Converter revision: `f369c7fe6d545640646839e7ee9bd62704b505f0`. |
|
|
| Citation: Reizenstein et al., *Common Objects in 3D: Large-Scale Learning and |
| Evaluation of Real-life 3D Category Reconstruction*, ICCV 2021. |
|
|
