论文标题

面部识别的调查

A Survey of Face Recognition

论文作者

Wang, Xinyi, Peng, Jianteng, Zhang, Sufang, Chen, Bihui, Wang, Yi, Guo, Yandong

论文摘要

近年来,与深度卷积神经网络见证了面部识别的突破。每年在FR领域发表数十篇论文。其中一些是在工业界应用的,并在人类生活中发挥了重要作用,例如设备解锁,移动支付等。本文介绍了面部识别,包括其历史,管道,基于传统手动设计的功能或深度学习,主流培训,评估数据集和相关应用程序的算法。我们已经分析并比较了最先进的作品,并仔细设计了一组实验,以找到骨干大小和数据分布的效果。这项调查是FG2023工业界的教程的材料。

Recent years witnessed the breakthrough of face recognition with deep convolutional neural networks. Dozens of papers in the field of FR are published every year. Some of them were applied in the industrial community and played an important role in human life such as device unlock, mobile payment, and so on. This paper provides an introduction to face recognition, including its history, pipeline, algorithms based on conventional manually designed features or deep learning, mainstream training, evaluation datasets, and related applications. We have analyzed and compared state-of-the-art works as many as possible, and also carefully designed a set of experiments to find the effect of backbone size and data distribution. This survey is a material of the tutorial named The Practical Face Recognition Technology in the Industrial World in the FG2023.

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