Qian Huang, George C. Stockman
ICPR 1994
We propose using Masked Auto-Encoder (MAE), a transformer model self-supervisedly trained on image inpainting, for anomaly detection (AD). Assuming anomalous regions are harder to reconstruct compared with normal regions. MAEDAY is the first image-reconstruction-based anomaly detection method that utilizes a pre-trained model, enabling its use for Few-Shot Anomaly Detection (FSAD). We also show the same method works surprisingly well for the novel tasks of Zero-Shot AD (ZSAD) and Zero-Shot Foreign Object Detection (ZSFOD), where no normal samples are available.
Qian Huang, George C. Stockman
ICPR 1994
Minerva M. Yeung, Fred Mintzer
ICIP 1997
Hagen Soltau, Lidia Mangu, et al.
ASRU 2011
Graham Mann, Indulis Bernsteins
DIMEA 2007