Seongdeok Bang

Memory-Distilled Selection for Noise-Robust Anomaly Detection

Anomaly detection (AD) under data contamination is critical for deploying unsupervised defect detection in industrial environments, where curating perfectly clean training sets is impractical. However, existing methods are sensitive to contamination, suffering significant performance degradation as …