Zhi-Xing Wu

Adaptive Loss Weighting for Unsupervised Industrial Anomaly Detection via Reverse Distillation

Due to the use of fixed loss weight allocation between different feature layers, unsupervised industrial surface anomaly detection often fails to capture multi-scale anomalies, resulting in the loss of fine-grained defects and severe background noise. To address this research gap, this paper proposes an unsupervised an...