Unified Unsupervised Anomaly Detection via Matching Cost Filtering

Zhe Zhang, Mingxiu Cai, Gaochang Wu +5

Unsupervised anomaly detection (UAD) aims to identify image- and pixel-level anomalies using only normal training data, with wide applications such as industrial inspection and med…