Yue-Zhou Wu

ShufflePaste: Four-Way Structural Disturbance Learning With Swin Transformer for Industrial Anomaly Detection

Industrial anomaly detection aims to identify defective samples that deviate from normal visual patterns, while real anomaly annotations are often scarce, costly, and incomplete in practical manufacturing scenarios. To address this challenge, this paper proposes ShufflePaste, a self-supervised representation learning f...