Aditya Malik, Nalini Ratha, et al.
CAI 2024
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.
Aditya Malik, Nalini Ratha, et al.
CAI 2024
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CVPR 2007
Rogerio Feris, Lisa M. Brown, et al.
ICPR 2014
Pavel Kisilev, Daniel Freedman, et al.
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