Zero-Shot Anomaly Detection via Learnable Complementary Prompts and Cross-Modal Interaction
Extensive experiments conducted on ten real-world industrial anomaly segmentation datasets demonstrate the superior performance of LCPCLIP in detecting anomalies without any prior knowledge of the dataset categories, which sets a new benchmark for adaptability and generalization in industrial applications.