Improving Face Recognition Using Pre-trained Models for Mask Wearer Images

M. Hongo, T. Goto
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Abstract

Wearing a mask hides half of the face, making it difficult to recognize it as a face in computer vision. There is a problem that it becomes impossible to identify the whereabouts of a person or an individual because it is not recognized as a face. In this paper, we aim to improve the recognition rate by using learning-based method and combining both NVIDIA's pre-trained model and face images with and without masks.
使用预先训练的面具佩戴者图像模型改进人脸识别
戴着面具会遮住一半的脸,很难在计算机视觉中识别出这是一张脸。有一个问题是,由于无法识别人脸,因此无法确定一个人或个人的下落。在本文中,我们的目标是利用基于学习的方法,结合NVIDIA的预训练模型和带面具和不带面具的人脸图像来提高识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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