Chengkan Lv

MRAD: Zero-Shot Anomaly Detection with Memory-Driven Retrieval

Zero-shot anomaly detection (ZSAD) often leverages pretrained vision or vision-language models, but many existing methods use prompt learning or complex modeling to fit the data distribution, resulting in high training or inference cost and limited cross-domain stability. To address these limitation…