| --- |
| license: other |
| license_name: scannetpp-terms-of-use |
| license_link: https://kaldir.vc.in.tum.de/scannetpp/ |
| tags: |
| - scannetpp |
| - 3d |
| - depth |
| viewer: false |
| --- |
| |
| # ScanNet++ iPhone depth maps |
|
|
| The iPhone LiDAR depth maps of ScanNet++ from `/data/ScanNetpp`, preserving their source filenames and directory |
| layout, so a download can be laid over a ScanNet++ copy. Files are uploaded without modification. |
|
|
| | Path | Files | Bytes | What | |
| |---|---:|---:|---| |
| | `data/*/iphone/depth.bin` | 968 | 608,124,587,157 | iPhone LiDAR depth | |
|
|
| Camera poses and intrinsics (`iphone/pose_intrinsic_imu.json`, `iphone/colmap/`) and the RGB video are not |
| included; they come with ScanNet++ itself. |
|
|
| ## Per-scene layout |
|
|
| ```text |
| data/<scene_id>/ |
| iphone/depth.bin LiDAR depth stream of the iPhone video |
| ``` |
|
|
| `iphone/depth.bin` is decoded into per-frame depth images by the official toolkit |
| (`iphone/prepare_iphone_data.py` in https://github.com/scannetpp/scannetpp). |
|
|
| ## Inventory |
|
|
| 968 files, 608,124,587,157 bytes over 968 scenes. `files_manifest.jsonl` records the relative path, byte count |
| and SHA-256 of every file. |
|
|
| ## Source and terms |
|
|
| Original dataset: [ScanNet++](https://kaldir.vc.in.tum.de/scannetpp/) (C. Yeshwanth, Y.-C. Liu, M. Nießner, A. Dai, |
| *ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes*, ICCV 2023). This copy retains the original ScanNet++ |
| Terms of Use; access is limited to users who have accepted them. |
|
|
