Transferable visual pattern memory network for domain adaptation in anomaly detection

Cangning Fan, Ye Jin, Peng Liu, Wei Zhao

Abstract: Highlights•This study focuses on a rarely studied anomaly detection transfer scenario with little supervised information.•An adversarial domain adaptation method is proposed to extract transferable visual patterns to transfer knowledge.•A self-supervised objective is integrated to enhance the discriminability of anomalies.