{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T10:39:35Z","timestamp":1779359975307,"version":"3.51.4"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T00:00:00Z","timestamp":1724803200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T00:00:00Z","timestamp":1724803200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,28]]},"DOI":"10.1109\/case59546.2024.10711763","type":"proceedings-article","created":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T17:40:16Z","timestamp":1729705216000},"page":"2123-2128","source":"Crossref","is-referenced-by-count":7,"title":["RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection"],"prefix":"10.1109","author":[{"given":"Yuqi","family":"Cheng","sequence":"first","affiliation":[{"name":"Huazhong University of Science and Technology,State Key Laboratory of Intelligence Manufacturing Equipment and Technology, School of Mechanical Science and Engineering,Wuhan,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunkang","family":"Cao","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology,State Key Laboratory of Intelligence Manufacturing Equipment and Technology, School of Mechanical Science and Engineering,Wuhan,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Chen","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology,State Key Laboratory of Intelligence Manufacturing Equipment and Technology, School of Mechanical Science and Engineering,Wuhan,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiming","family":"Shen","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology,State Key Laboratory of Intelligence Manufacturing Equipment and Technology, School of Mechanical Science and Engineering,Wuhan,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"A survey on visual anomaly detection: Challenge, approach, and prospect","author":"Cao","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02159"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20056-4_23"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00982"},{"key":"ref5","article-title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","author":"Zhang","year":"2023"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3343832"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2024.3357213"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP46576.2022.9897283"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ac8ac1"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ac39d0"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICUMT54235.2021.9631567"},{"key":"ref12","first-page":"3586","article-title":"The eyecandies dataset for unsupervised multimodal anomaly detection and localization","volume-title":"Proceedings of the Asian Conference on Computer Vision","author":"Bonfiglioli"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00188"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01359"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00951"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02348"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19821-2_31"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2023.3241579"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01392"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2021.3094452"},{"key":"ref21","article-title":"Segment any anomaly without training via hybrid prompt regularization","author":"Cao","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01878"},{"key":"ref23","article-title":"A zero-\/few-shot anomaly classification and segmentation method for cvpr 2023 vand workshop challenge tracks 1&2: 1st place on zero-shot ad and 4th place on few-shot ad","author":"Chen","year":"2023"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-023-1459-z"}],"event":{"name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","location":"Bari, Italy","start":{"date-parts":[[2024,8,28]]},"end":{"date-parts":[[2024,9,1]]}},"container-title":["2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10711304\/10711288\/10711763.pdf?arnumber=10711763","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T01:59:34Z","timestamp":1732672774000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10711763\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,28]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/case59546.2024.10711763","relation":{},"subject":[],"published":{"date-parts":[[2024,8,28]]}}}