VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization

04/20/2021
by   Pankaj Mishra, et al.
13

We present a transformer-based image anomaly detection and localization network. Our proposed model is a combination of a reconstruction-based approach and patch embedding. The use of transformer networks helps to preserve the spatial information of the embedded patches, which are later processed by a Gaussian mixture density network to localize the anomalous areas. In addition, we also publish BTAD, a real-world industrial anomaly dataset. Our results are compared with other state-of-the-art algorithms using publicly available datasets like MNIST and MVTec.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset