Computer personnel research - Issues and progress in the 60's
David B. Mayer, Ashford W. Stalnaker
ACM SIGMIS CPR 1967
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.
David B. Mayer, Ashford W. Stalnaker
ACM SIGMIS CPR 1967
Paul A. Karger
SOUPS 2006
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
Peter L. Williams, Nelson L. Max, et al.
IEEE TVCG