Informative knowledge distillation for image anomaly segmentation

Unsupervised anomaly segmentation methods based on knowledge distillation have recently been developed and have shown superior segmentation performance. However, little attention has been paid to the overfitting problem caused by the inconsistency between the capacity of a neural network and the amount of knowledge in this scheme. This study proposes a novel method called informative knowledge distillation (IKD) to address the overfitting …