Jongmin Yu

Prototype-Guided Diffusion Model for Multi-Class Unsupervised Anomaly Detection

Unsupervised Anomaly detection is important in industrial inspection and automation, where defects are rare, stochastic, and costly to annotate, while nominal data are abundant. Diffusion models have shown strong potential for unsupervised anomaly detection, where only normal data are available for training. However, s...