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A Comparative Study of Face Detection Algorithms for Masked Face Detection

arXiv 2305.11077 ↗First posted 18 May 2023cs.CV cs.LGcited by 0

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Abstract (arXiv)

Contemporary face detection algorithms have to deal with many challenges such as variations in pose, illumination, and scale. A subclass of the face detection problem that has recently gained increasing attention is occluded face detection, or more specifically, the detection of masked faces. Three years on since the advent of the COVID-19 pandemic, there is still a complete lack of evidence regarding how well existing face detection algorithms perform on masked faces. This article first offers a brief review of state-of-the-art face detectors and detectors made for the masked face problem, along with a review of the existing masked face datasets. We evaluate and compare the performances of a well-representative set of face detectors at masked face detection and conclude with a discussion on the possible contributing factors to their performance.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 35 of its 62 references that are in the map. First posted on arXiv 18 May 2023.

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35 of 62 references.

References · 35

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23 more
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