  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.
