• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Song, Lin (Song, Lin.) | Yang, Jin-Fu (Yang, Jin-Fu.) | Shang, Qing-Zhen (Shang, Qing-Zhen.) | Li, Ming-Ai (Li, Ming-Ai.)

收录:

EI Scopus

摘要:

Face detection has achieved tremendous strides thanks to convolutional neural networks. However, dense face detection remains an open challenge due to large face scale variation, tiny faces, and serious occlusion. This paper presents a robust, dense face detector using global context and visual attention mechanisms which can significantly improve detection accuracy. Specifically, a global context fusion module with top-down feedback is proposed to improve the ability to identify tiny faces. Moreover, a visual attention mechanism is employed to solve the problem of occlusion. Experimental results on the public face datasets WIDER FACE and FDDB demonstrate the effectiveness of the proposed method. © 2022, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature.

关键词:

Face recognition Behavioral research Computer vision Deep learning Convolutional neural networks

作者机构:

  • [ 1 ] [Song, Lin]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Yang, Jin-Fu]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Yang, Jin-Fu]Beijing Key Laboratory of Computational Intelligence and Intelligent Systems, Beijing; 100124, China
  • [ 4 ] [Shang, Qing-Zhen]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Li, Ming-Ai]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

Machine Intelligence Research

ISSN: 2731-538X

年份: 2022

期: 3

卷: 19

页码: 247-256

被引次数:

WoS核心集被引频次:

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 1

归属院系:

在线人数/总访问数:562/4955957
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司