Detecting Face with Densely Connected Face Proposal Network

doi:10.1016/j.neucom.2018.01.012

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

	Detecting Face with Densely Connected Face Proposal Network
	Zhang, Shifeng1,2,3 ; Zhu, Xiangyu1,2,3 ; Lei, Zhen1,2,3 ; Wang, Xiaobo1,2,3 ; Shi, Hailin1,2,3 ; Li, Stan Z.1,2,3
刊名	NEUROCOMPUTING
	2018-04-05
卷号	284 页码:119-127
关键词	Face Detection Small Face Region Proposal Network
DOI	10.1016/j.neucom.2018.01.012
文献子类	Article
英文摘要	Accuracy and efficiency are two conflicting challenges for face detection, since effective models tend to be computationally prohibitive. To address these two conflicting challenges, our core idea is to shrink the input image and focus on detecting small faces. Reducing the image resolution can significantly improve the detection speed, but it also results in smaller faces that need to pay more attention. Specifically, we propose a novel face detector, dubbed the name Densely Connected Face Proposal Network (DCFPN), with high accuracy as well as CPU real-time speed. Firstly, we subtly design a lightweight-but-powerful fully convolution network with the consideration of efficiency and accuracy. Secondly, we present a dense anchor strategy and a scale-aware anchor matching scheme to improve the recall rate of small faces. Finally, a fair L1 loss is introduced to locate small faces well. As a consequence, our proposed method can detect faces at 30 FPS on a single 2.60 GHz CPU core and 250 FPS using a GPU for the VGA-resolution images. We achieve state-of-the-art performance on the common face detection benchmark datasets. (C) 2018 Elsevier B.V. All rights reserved.
WOS关键词	WILD
WOS研究方向	Computer Science
语种	英语
WOS记录号	WOS:000425883300013
资助机构	National Key Research and Development Plan(2016YFC0801002) ; Chinese National Natural Science Foundation(61473291 ; AuthenMetric RD Funds ; 61572501 ; 61502491 ; 61572536)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/21950]
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
作者单位	1.Chinese Acad Sci, CBSR, Inst Automat, Beijing, Peoples R China 2.Chinese Acad Sci, NLPR, Inst Automat, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shifeng,Zhu, Xiangyu,Lei, Zhen,et al. Detecting Face with Densely Connected Face Proposal Network[J]. NEUROCOMPUTING,2018,284:119-127.
APA	Zhang, Shifeng,Zhu, Xiangyu,Lei, Zhen,Wang, Xiaobo,Shi, Hailin,&Li, Stan Z..(2018).Detecting Face with Densely Connected Face Proposal Network.NEUROCOMPUTING,284,119-127.
MLA	Zhang, Shifeng,et al."Detecting Face with Densely Connected Face Proposal Network".NEUROCOMPUTING 284(2018):119-127.