Reducing modal differences in zero-shot Anomaly detection based on vision-language generation model

Zero-shot anomaly detection methods based on vision-language model rely on alignment between image and text. These methods ignore the inherent differences between different modalities, which is unfavorable for improving the alignment between modalities. This paper reduces modal differences between image and text by using guiding vision feature and text feature from the pre-trained vision-language generation model. The vision perception text …