Chang-Long Jin

PL-SCEA: Reconfiguring Pretrained Attention for Few-Shot Industrial Anomaly Detection

Vision Foundation Models (VFMs) provide transferable patch representations for few-shot industrial anomaly detection, but their attention computation is typically inherited from pretraining objectives centered on semantic aggregation. This creates a potential mismatch: token relations that support semantic recognition...