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Datasets

Datasets should have the following structure.

The triplane folder is created by scripts/save_triplane.py after scripts/train_ae_main.py.

SemanticKITTI

You can download SemanticKITTI datasets from here.

If you want to do semantic scene completion refinement, place the .label file from ssc method(e.g. monoscene, occdepth, scpnet, ssasc) in the following structure.

/dataset/
    └── sequences/
        ├── 00/
        |   ├── voxels/
        │   |     ├ 000000.label
        │   |     ├ 000000.invalid
        │   ├── monoscene/
        │   |     ├ 000000.label
        │   ├── occdepth/
        │   |     ├ 000000.label
        │   ├── scpnet/
        │   |     ├ 000000.label
        │   ├── ssasc/
        │   |     ├ 000000.label
        │   └── triplane/
        │         ├ 000000.npy
        │         ├ 000000_monoscene.npy
        │         ├ 000000_occdepth.npy
        │         ├ 000000_scpnet.npy
        │         ├ 000000_ssasc.npy
        ├── 01/
        .
        .
        └── 10/

CarlaSC

You can download CarlaSC Cartesian datasets from here.

The structure differs slightly from the original CarlaSC dataset to align with the SemanticKITTI dataset. The voxels folder was originally the evaluation folder, which contains the GT for semantic scene completion.

/carla/
    └── sequences/
        ├── Town01_Heavy/
        |   ├── voxels/
        │   |     ├ 000000.label
        │   |     ├ 000000.bin
        │   └── triplane/
        │         ├ 000000.npy
        ├── Town01_Medium/
        .
        .
        └── Town10_Light/