Paul A. Karger
SOUPS 2006
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.
Paul A. Karger
SOUPS 2006
Konstantinos Tarabanis, Roger Y. Tsai, et al.
Computer Vision and Image Understanding
Xiaohui Shen, Gang Hua, et al.
FG 2011
Alex Cozzi, Florentin Wörgötter
IJCV