Semantic Scholar Open Access 2021 464 sitasi

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

P. Mishra Riccardo Verk Daniele Fornasier C. Piciarelli G. Foresti

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Abstrak

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 preserving the spatial information of the embedded patches, which is 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.

Topik & Kata Kunci

Computer Science

Penulis (5)

P. Mishra

Riccardo Verk

Daniele Fornasier

C. Piciarelli

G. Foresti

Format Sitasi

APA MLA BibTeX

Mishra, P., Verk, R., Fornasier, D., Piciarelli, C., Foresti, G. (2021). VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization. https://doi.org/10.1109/ISIE45552.2021.9576231

Akses Cepat

Lihat di Sumber doi.org/10.1109/ISIE45552.2021.9576231

Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Total Sitasi: 464×
Sumber Database: Semantic Scholar
DOI: 10.1109/ISIE45552.2021.9576231
Akses: Open Access ✓