计算机工程与应用2020，Vol.56Issue(1)：203-208,6.DOI:10.3778/j.issn.1002-8331.1810-0035
复杂场景下基于R-FCN的小人脸检测研究
Research on Small Face Detection Based on R-FCN in Complex Scenes
摘要
Abstract
Accurate detection of small, blurred and partially occluded faces in complex scenes is still a problem with face detection algorithms. To this end, this paper proposes a face-detection algorithm based on the region-based fully convolu-tional network R-FCN to solve the small face detection problem. The complete convolution residual network ResNet is used as the backbone network, and a variety of new technologies are integrated, including the Squeeze-and-Excitation module and the residual attention mechanism to improve the final output accuracy. Tested on the most challenging face detection benchmark Widerface dataset, the results show that the proposed algorithm has excellent face detection effect in complex scenes, and it is also robust to partial occlusion, blur and face pose changes.关键词
人脸检测/区域全卷积神经网络/残差网络/复杂场景Key words
face detection/region-based fully convolutional network/ResNet/complex scenes分类
信息技术与安全科学引用本文复制引用
李静,降爱莲..复杂场景下基于R-FCN的小人脸检测研究[J].计算机工程与应用,2020,56(1):203-208,6.基金项目
山西省回国留学人员科研资助项目(No.2017-051). （No.2017-051）
