A Survey of Visual Sensory Anomaly Detection

• URL: http://arxiv.org/abs/2202.07006v1
• Date: Mon, 14 Feb 2022 19:50:03 GMT
• Title: A Survey of Visual Sensory Anomaly Detection
• Authors: Xi Jiang, Guoyang Xie, Jinbao Wang, Yong Liu, Chengjie Wang, Feng Zheng, Yaochu Jin
• Abstract summary: Visual sensory anomaly detection (AD) is an essential problem in computer vision. We provide a comprehensive review of visual sensory AD and category into three levels according to the form of anomalies.
• Score: 53.23336329817023
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Visual sensory anomaly detection (AD) is an essential problem in computer vision, which is gaining momentum recently thanks to the development of AI for good. Compared with semantic anomaly detection which detects anomaly at the label level (semantic shift), visual sensory AD detects the abnormal part of the sample (covariate shift). However, no thorough review has been provided to summarize this area for the computer vision community. In this survey, we are the first one to provide a comprehensive review of visual sensory AD and category into three levels according to the form of anomalies. Furthermore, we classify each kind of anomaly according to the level of supervision. Finally, we summarize the challenges and provide open directions for this community. All resources are available at https://github.com/M-3LAB/awesome-visual-sensory-anomaly-detection.

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