2024
CAGEN: Controllable Anomaly Generator using Diffusion Model
ICASSP 2024accepted
Data augmentation has been widely applied in anomaly detection, which generates synthetic anomalous data for training. However, most existing anomaly augmentation methods focus on image-level cut-and-paste techniques, resulting in less realistic synthetic results, and are restricted to a few predefi…