Anomaly Detection via Reverse Distillation from One-Class Embedding. (arXiv:2201.10703v1 [cs.CV])

Knowledge distillation (KD) achieves promising results on the challenging
problem of unsupervised anomaly detection (AD).The representation discrepancy
of anomalies in the teacher-student (T-S) model provides essential evidence for
AD. However, using similar or identical architectures to build the teacher and
student models in previous studies hinders the diversity of anomalous
representations. To tackle this problem, we propose a novel T-S model
consisting of a teacher encoder and a student decoder and introduce a simple
yet effective "reverse distillation" paradigm accordingly. …

anomaly detection arxiv cv detection distillation embedding