FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data

Jiin Im, Yongho Son, Je Hyeong Hong

While the mainstream research in anomaly detection has mainly followed the one-class classification, practical industrial environments often incur noisy training data due to annota…