Masked Transformer for Image Anomaly Localization.Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset. 
Masked Transformer
We thus propose a new model based on the Vision Transformer architecture with patch masking: the input image is split in several patches, and each patch is reconstructed only from the surrounding data, thus ignoring the potentially anomalous information contained in the patch itself. 
Vision Transformer
The proposed model has been tested on popular anomaly detection datasets such as MVTec and head CT and achieved good results when compared to other state-of-the-art approaches.
MVTec