Dual-Image Enhanced CLIP for Zero-Shot Anomaly Detection

arXiv:2405.04782v1 Announce Type: new
Abstract: Image Anomaly Detection has been a challenging task in Computer Vision field. The advent of Vision-Language models, particularly the rise of CLIP-based frameworks, has opened new avenues for zero-shot anomaly detection. Recent studies have explored the use of CLIP by aligning images with normal and prompt descriptions. However, the exclusive dependence on textual guidance often falls short, highlighting the critical importance of additional visual references. In this work, we introduce a Dual-Image Enhanced CLIP approach, …

abstract anomaly anomaly detection arxiv clip computer computer vision cs.cv detection frameworks however image images language language models normal prompt studies type vision vision-language vision-language models zero-shot