Qianhao Luo

Dual-Prototype-Guided Multi-task Learning for Unsupervised Anomaly Detection and Classification

Unsupervised Anomaly Detection (UAD) and anomaly classification are frequently used in industrial and medical scenarios. Specifically, UAD identifies anomalous regions at the fine-grained pixel-level, while anomaly classification distinguishes anomaly types at the anomaly region level. However, exis