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Yuanyi Duan

1 accepted papers

2026

One-to-More: High-Fidelity Training-Free Anomaly Generation with Attention Control

CVPR 2026

Industrial anomaly detection (AD) is characterized by an abundance of normal images but a scarcity of anomalous ones. Although numerous few-shot anomaly synthesis methods have been proposed to augment anomalous data for downstream AD tasks, most existing approaches require time-consuming training an

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