Visual structural anomaly detection based on lightweight image restoration network

Qiliang Wu; Dongce Fei

doi:10.1117/12.3034078

13 June 2024 Visual structural anomaly detection based on lightweight image restoration network

Qiliang Wu, Dongce Fei

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131800T (2024) https://doi.org/10.1117/12.3034078
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Currently, reconstruction-based visual anomaly detection tends to use more complex models to improve the accuracy of the model. This paper proposes a lightweight image restoration network to reduce the network model's parameters and computational complexity, and puts forward the feature similarity loss to reduce the impact of noise on the accuracy of anomaly detection discrimination. Experimental results show that the proposed method uses fewer parameters and computational complexity, achieving results close to RIAD.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiliang Wu and Dongce Fei "Visual structural anomaly detection based on lightweight image restoration network", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131800T (13 June 2024); https://doi.org/10.1117/12.3034078

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