Anomaly detection aims to find instances that are considered unusual and is a fundamental
problem of data science. Recently, deep anomaly detection methods were shown to achieve …

The recent rapid development of deep learning has laid a milestone in industrial image
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …

The state-of-the-art in discriminative unsupervised surface anomaly detection relies on
external datasets for synthesizing anomaly-augmented training images. Such approaches …

Anomaly detection is an active research field in industrial defect detection and medical
disease detection. However, previous anomaly detection works suffer from unstable training …

Anomalies are ubiquitous in all scientific fields and can express an unexpected event due to
incomplete knowledge about the data distribution or an unknown process that suddenly …

The essence of unsupervised anomaly detection is to learn the compact distribution of
normal samples and detect outliers as anomalies in testing. Meanwhile, the anomalies in …