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- SeaS Public
[arXiv:2410.14987] SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning. Paper is available at https://arxiv.org/abs/2410.14987
HUST-SLOW/SeaS’s past year of commit activity - MuSc Public
[ICLR2024] MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images (The original repo is available at https://github.com/xrli-U/MuSc)
HUST-SLOW/MuSc’s past year of commit activity - AnomalyNCD Public
[arXiv:2410.14379] AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios. Paper is available at https://arxiv.org/abs/2410.14379
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