计算机与数字工程2024，Vol.52Issue(2)：315-320,6.DOI:10.3969/j.issn.1672-9722.2024.02.003
基于超分辨率重建的低分辨率人脸检测算法
Low-resolution Face Detection Algorithm Based on Super-resolution Reconstruction
摘要
Abstract
Low-resolution face detection has important applications in video surveillance and other fields.However,current face detection algorithms are not ideal in low-resolution face detection.For this problem,the paper proposes a low-resolution face detection algorithm based on super-resolution reconstruction.First,most of the normal faces can be detected by the prepositioned basic face detector.Secondly,by lowering the category confidence threshold.the regions proposal that may contain faces are sent to the super-resolution reconstruction network(MGAN)based on the improved GAN to further complete the face detection task.Final-ly,the face regions are summarized and the non-maximum suppression algorithm is used to obtain the final detection results.The ex-perimental results show that in the WIDERFACE data set,compared with the mainstream face detection algorithms such as S3FD,the proposed algorithms have higher detection accuracy,and the improvement is obvious in the hard subset.关键词
超分辨率重建/生成对抗网络/人脸检测/低分辨率Key words
super-resolution/generative adversarial net/face detection/low-resolution分类
信息技术与安全科学引用本文复制引用
王国辉,陈健美..基于超分辨率重建的低分辨率人脸检测算法[J].计算机与数字工程,2024,52(2):315-320,6.基金项目
国家自然科学基金项目(编号:61702229) （编号:61702229）
江苏省自然科学基础研究计划基金项目(编号:BK20150531)资助. （编号:BK20150531）
