Shengchuan Zhang

Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection

2024 · arXiv (Cornell University)

Due to the scarcity and unpredictable nature of defect samples, industrial anomaly detection (IAD) predominantly employs unsupervised learning. However, all unsupervised IAD methods face a common challenge: the inherent bias in normal samples, which causes …