Contrastive Knowledge Distillation for Anomaly Detection in Multi-Illumination/Focus Display Images
This paper proposes a novel contrastive learning scheme for knowledge distillation-based anomaly detection, namely Multiresolution Contrastive Distillation (MCD), which does not require positive/negative pairs with an anchor but operates by pulling/pushing the distance between the teacher and student features.