Min Meng

Dynamic concept memory and contrastive feature generation for robust generalized zero-shot learning

UAD: A Unified Model for Zero-Shot Anomaly Detection

Zero-shot anomaly detection (ZSAD) aims to identify and localize anomalies in previously unseen target domains without accessing any target-domain training data, which is crucial under privacy, security, or proprietary constraints. However, existing ZSAD methods often struggle to generalize across domains, as they are...