Masked Transformer for image Anomaly Localization

Understand

Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset.

• The task is of practical importance for various real-life applications like biomedical image analysis, visual inspection in industrial production, banking, traffic management, etc.
• Most of the current deep learning approaches rely on image reconstruction: the input image is projected in some latent space and then reconstructed, assuming that the network (mostly trained on normal data) will not be able to reconstruct the anomalous portions.
• However, this assumption does not always hold.