Data-Aware Optimization for Dual-Frozen ViT Distillation in Unsupervised Anomaly Detection*
Teacher-student distillation based on normal samples has been widely adopted in Unsupervised Anomaly Detection (UAD). Incorporating Vision Transformers (ViTs) into this task enhances global representation capability; however, existing methods still suffer from feature instability caused by pseudo-activation phenomena a...