MST: Multiscale Flow-Based Student–Teacher Network for Unsupervised Anomaly Detection
Yi Yang,
Yi Yang,
Shubo Zhou
et al.
Abstract:Student–teacher networks have shown promise in unsupervised anomaly detection; however, issues such as semantic confusion and abnormal deformations still restrict the detection accuracy. To address these issues, we propose a novel student–teacher network named MST by integrating the multistage pixel-reserving bridge (MPRB) and the spatial compression autoencoder (SCA) to the MMR network. The MPRB enhances inter-level information interaction and local feature extraction, improving the anomaly localization and r… Show more
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