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
2018-04-05
发表期刊NEUROCOMPUTING
卷号284页码:119-127
文章类型Article
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.
关键词Face Detection Small Face Region Proposal Network
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2018.01.012
关键词[WOS]WILD
收录类别SCI
语种英语
项目资助者National Key Research and Development Plan(2016YFC0801002) ; Chinese National Natural Science Foundation(61473291 ; AuthenMetric RD Funds ; 61572501 ; 61502491 ; 61572536)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000425883300013
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/21950
专题模式识别国家重点实验室_生物识别与安全技术研究
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
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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.
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