2026
VisualAD: Language-Free Zero-Shot Anomaly Detection via Vision Transformer
CVPR 2026
Zero-shot anomaly detection (ZSAD) requires detecting and localizing anomalies without access to target-class anomaly samples. Mainstream methods rely on vision-language models (VLMs) such as CLIP: they build hand-crafted or learned prompt sets for normal and abnormal semantics, then compute image-t