Consistent Sub-Decision Network for Low-Quality Masked Face Recognition

doi:10.1109/LSP.2022.3170246

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 生物识别与安全技术研究中心

	Consistent Sub-Decision Network for Low-Quality Masked Face Recognition
	Zhao, Weisong 5,6; Zhu, Xiangyu 2,3; Shi, Haichao 4; Zhang, Xiao-Yu 4; Lei, Zhen 1,2,3
刊名	IEEE SIGNAL PROCESSING LETTERS
	2022
卷号	29 页码:1147-1151
关键词	Face recognition Faces Feature extraction Facial features Training Knowledge engineering Drives COVID-19 masked face recognition low-quality
ISSN号	1070-9908
DOI	10.1109/LSP.2022.3170246
通讯作者	Lei, Zhen(zlei@nlpr.ia.ac.cn)
英文摘要	The COVID-19 pandemic makes wearing masks mandatory in supermarkets, pharmacies, public transport, etc. Existing facial recognition systems encounter severe performance degradation as the masks occlude key facial regions. Recently, simulation-based methods are proposed to generate masked faces from unmasked faces. However, among simulated faces, there are low-quality samples with negative occlusion, which leads to ambiguous or absent facial features. In this paper, we propose a consistent sub-decision network to obtain sub-decisions that correspond to different facial regions and constrain sub-decisions by weighted bidirectional KL divergence to make the network concentrate on the upper faces without occlusion. In addition, we perform knowledge distillation to drive the masked face embeddings towards an approximation of the original data distribution to mitigate the information loss. Experiments show that the proposed method performs better than the baseline on public masked face recognition datasets, i.e., RMFD, MFR2, and MLFW.
资助项目	National Key Research & Development Program[2020YFC2003901] ; National Natural Science Foundation of China[61871378] ; National Natural Science Foundation of China[U2003111] ; National Natural Science Foundation of China[61876178] ; National Natural Science Foundation of China[61872367] ; National Natural Science Foundation of China[62176256] ; National Natural Science Foundation of China[62106264] ; National Natural Science Foundation of China[61976229] ; Youth Innovation Promotion Association CAS[Y2021131] ; InnoHK Program
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000793787300005
资助机构	National Key Research & Development Program ; National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS ; InnoHK Program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/49368]
专题	自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心
通讯作者	Lei, Zhen
作者单位	1.Chinese Acad Sci, Hong Kong Inst Sci & Innovat, Ctr Artificial Intelligence & Robot, Hong Kong, Peoples R China 2.Univ Chinese Acad Sci UCAS, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, CBSR NLPR, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Informat Engn, Beijing 100093, Peoples R China 5.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100049, Peoples R China 6.Chinese Acad Sci, Inst Informat Engn, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Weisong,Zhu, Xiangyu,Shi, Haichao,et al. Consistent Sub-Decision Network for Low-Quality Masked Face Recognition[J]. IEEE SIGNAL PROCESSING LETTERS,2022,29:1147-1151.
APA	Zhao, Weisong,Zhu, Xiangyu,Shi, Haichao,Zhang, Xiao-Yu,&Lei, Zhen.(2022).Consistent Sub-Decision Network for Low-Quality Masked Face Recognition.IEEE SIGNAL PROCESSING LETTERS,29,1147-1151.
MLA	Zhao, Weisong,et al."Consistent Sub-Decision Network for Low-Quality Masked Face Recognition".IEEE SIGNAL PROCESSING LETTERS 29(2022):1147-1151.