One-class classification (OCC) aims to learn an effective data description enclose all normal training samples and detect anomalies based on the deviation from description. Current state-of-the-art OCC models a compact normality by hyper-sphere minimisation, but they often suffer overfitting data, especially when set is small or contaminated with anomalous samples. To address this issue, we int...