ICCV 2023 Open Access Repository
ICCV 2023 open access These ICCV 2023 workshop papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. Powered by: Sponsored by: MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection Tianpeng Bao, Jiadong Chen, Wei Li, Xiang Wang, Jingjing Fei, Liwei Wu, Rui Zhao, Ye Zheng; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2023, pp. 993-1002 Abstract Visual anomaly detection plays a crucial role in not only manufacturing inspection to find defects
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