| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - 3d-anomaly-detection |
| - point-cloud |
| - real3d-ad |
| - af3ad |
| --- |
| |
| # AF3AD Checkpoints |
|
|
| Pretrained AF3AD PO3AD-style checkpoints for Real3D-AD. AF3AD was accepted to ECCV 2026. |
|
|
| These files are discriminator-only PyTorch `state_dict` checkpoints, packaged with a small YAML config per category. |
|
|
| ## Usage |
|
|
| Clone or download this repository into the project as `ckpts/`: |
|
|
| ```text |
| ckpts/Real3DAD/[category]/ckpts/[category].pth |
| ckpts/Real3DAD/[category]/po3ad_eval_real3d.yaml |
| ``` |
|
|
| From the AF3AD repo root: |
|
|
| ```bash |
| export PYTHONPATH="$PWD:$PYTHONPATH" |
| python3 scripts/evaluate_po3ad_checkpoint.py --checkpoint ckpts/Real3DAD/airplane/ckpts/airplane.pth --config ckpts/Real3DAD/airplane/po3ad_eval_real3d.yaml |
| ``` |
|
|
| Replace `airplane` with any available Real3D-AD category. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{balapour2026anomalyfactory3dmodular, |
| title={Anomaly Factory 3D: A Modular Framework for Diverse Pseudo-Anomaly Synthesis in Unsupervised 3D Anomaly Detection}, |
| author={Ali Balapour and Faraz Hach}, |
| year={2026}, |
| eprint={2606.29181}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV} |
| } |
| ``` |
|
|
