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

被引：216

作者：

Mishra, Pankaj ^{[1
]}

Verk, Riccardo ^{[1
]}

Fornasier, Daniele ^{[2
]}

Piciarelli, Claudio ^{[1
]}

Foresti, Gian Luca ^{[1
]}

机构：

[1] Univ Udine, Udine, Italy

[2] BeanTech Srl, Udine, UD, Italy

来源：

PROCEEDINGS OF 2021 IEEE 30TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2021年

关键词：

Anomaly Detection; Anomaly segmentation; Vision transformer; Gaussian density approximation; Anomaly dataset;

D O I：

10.1109/ISIE45552.2021.9576231

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页数：6

共 31 条

[1] Latent Space Autoregression for Novelty Detection [J].

Abati, Davide ;

Porrello, Angelo ;

Calderara, Simone ;

Cucchiara, Rita .

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, :481-490

[2] The effects of adding noise during backpropagation training on a generalization performance [J].

An, GZ .

NEURAL COMPUTATION, 1996, 8 (03) :643-674

[3]

[Anonymous], 2012, P ICML WORKSH UNS TR

[4]

Aytekin C, 2018, IEEE IJCNN

[5] Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings [J].

Bergmann, Paul ;

Fauser, Michael ;

Sattlegger, David ;

Steger, Carsten .

2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, :4182-4191

[6] Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders [J].

Bergmann, Paul ;

Loewe, Sindy ;

Fauser, Michael ;

Sattlegger, David ;

Steger, Carsten .

PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5, 2019, :372-380

[7] MVTec AD - A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection [J].

Bergmann, Paul ;

Fauser, Michael ;

Sattlegger, David ;

Steger, Carsten .

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, :9584-9592

[8]

BISHOP C M, 1994, Mixture density networks

[9]

Chalapathy R., 2018, Anomaly detection using one-class neural networks

[10] Distributed Real-Time Anomaly Detection in Networked Industrial Sensing Systems [J].

Chen, Po-Yu ;

Yang, Shusen ;

McCann, Julie A. .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2015, 62 (06) :3832-3842

← 1 2 3 4 →