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FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection

Image reconstruction-based anomaly detection models are widely explored in industrial visual inspection. However, existing models usually suffer from the trade-off between normal reconstruction fidelity and abnormal reconstruction distinguishability, which damages the performance.

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Cite this as

Tongkun Liua, Bing Lia, Xiao Dua, Bingke Jianga, Leqi Genga, Feiyang Wang, Zhuo Zhaoa (2024). Dataset: FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection. https://doi.org/10.57702/ohq0cmal

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2309.07068
Author	Tongkun Liua
More Authors	Bing Lia Xiao Dua Bingke Jianga Leqi Genga Feiyang Wang Zhuo Zhaoa
Homepage	https://github.com/liutongkun/FAIR