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arXiv · 2104.10036

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

Pankaj Mishra·Riccardo Verk·Daniele Fornasier·Claudio Piciarelli·Gian Luca Foresti
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Abstract

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.

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Pankaj Mishra, Riccardo Verk, Daniele Fornasier, Claudio Piciarelli, Gian Luca Foresti. 2021-04-20. VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization. https://doi.org/10.1109/isie45552.2021.9576231

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