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license: apache-2.0

3D-IDE Training Data

Complete, verified training data for 3D-IDE (CVPR 2026). This is the exact data used in our experiments — byte-identical to our training server. Use md5_manifest.txt / md5_manifest_scannet.txt to verify your local copy without re-downloading.

ScanNet notice: scannet/ archives and parts of the metadata are derived from ScanNet. By downloading them you agree to the ScanNet Terms of Use.

Contents

File Size Contents (archive-internal paths) Extract into
3d_ide_data.zip 4.3 GB processed/, metadata/, benchmark/, balanced/, embodiedscan/, multi.yaml data/
scannet/scannet_posed_images_part1.zip ~25 GB posed_images/scene0000_00 … (first half) data/scannet/
scannet/scannet_posed_images_part2.zip ~25 GB posed_images/… (second half) data/scannet/
scannet/scannet_mask_pcd.zip ~10 GB mask/, pcd_with_object_aabbs/ data/scannet/
vggt_features/vggt_features_part{1..9}.zip 9 × ~43 GB scene…/vggt_sliced.npy (no wrapper dir!) data/scannet/posed_images_3d_feature_vggt/
md5_manifest.txt MD5 of every file in 3d_ide_data.zip
md5_manifest_scannet.txt MD5 of every raw file under scannet/

The loose processed/, metadata/, benchmark/, balanced/ folders in this repo mirror the contents of 3d_ide_data.zip for convenient single-file access.

Extraction

Run from the repo root of 3D-IDE:

cd 3D-IDE

# 1. main data
unzip 3d_ide_data.zip -d data/

# 2. scannet raw data
unzip scannet_posed_images_part1.zip -d data/scannet/
unzip scannet_posed_images_part2.zip -d data/scannet/
unzip scannet_mask_pcd.zip          -d data/scannet/

# 3. VGGT features (note: archives contain scene dirs directly, no wrapper)
mkdir -p data/scannet/posed_images_3d_feature_vggt
for i in 1 2 3 4 5 6 7 8 9; do
    unzip vggt_features_part$i.zip -d data/scannet/posed_images_3d_feature_vggt/
done

Verify (instead of re-downloading)

If you already prepared data and want to check it matches ours exactly:

cd 3D-IDE/data
md5sum -c md5_manifest.txt           # json / metadata / embodiedscan
md5sum -c md5_manifest_scannet.txt   # posed_images / mask / pcd

Any FAILED line points at a file that differs from our training copy.

Not included (download separately)

Item Where
data/models/LLaVA-Video-7B-Qwen2/ lmms-lab/LLaVA-Video-7B-Qwen2
VGGT_checkpoints/model.pt facebook/VGGT-1B

Final layout

3D-IDE/
├── data/
│   ├── balanced/
│   ├── benchmark/
│   ├── embodiedscan/
│   ├── metadata/
│   ├── models/LLaVA-Video-7B-Qwen2/      # separate download
│   ├── processed/
│   ├── multi.yaml
│   └── scannet/
│       ├── mask/
│       ├── pcd_with_object_aabbs/
│       ├── posed_images/
│       └── posed_images_3d_feature_vggt/
└── VGGT_checkpoints/model.pt             # separate download