Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies

Hyuntae Kim, Changhee Lee

Unsupervised anomaly detection is a daunting task, as it relies solely on normality patterns from the training data to identify unseen anomalies during testing. Recent approaches h…