Knowledge Commons of Institute of Automation,CAS
SFD: Single Shot Scale-invariant Face Detector | |
Shifeng Zhang; Xiangyu Zhu; Zhen Lei; Hailin Shi; Xiaobo Wang; Stan Z. Li | |
2017 | |
会议名称 | IEEE International Conference on Computer Vision |
会议日期 | Oct. 22-29, 2017 |
会议地点 | Venice |
摘要 | This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (SFD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchor-based detectors deteriorate dramatically as the objects become smaller. We make contributions in the following three aspects: 1) proposing a scale-equitable face detection framework to handle different scales of faces well. We tile anchors on a wide range of layers to ensure that all scales of faces have enough features for detection. Besides, we design anchor scales based on the effective receptive field and a proposed equal proportion interval principle; 2) improving the recall rate of small faces by a scale compensation anchor matching strategy; 3) reducing the false positive rate of small faces via a max-out background label. As a consequence, our method achieves state-of-the-art detection performance on all the common face detection benchmarks, including the AFW, PASCAL face, FDDB and WIDER FACE datasets, and can run at 36 FPS on a Nvidia Titan X (Pascal) for VGA-resolution images. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/20046 |
专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
通讯作者 | Zhen Lei |
作者单位 | Institute of Automation Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Shifeng Zhang,Xiangyu Zhu,Zhen Lei,et al. SFD: Single Shot Scale-invariant Face Detector[C],2017. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Zhang_S3FD_Single_Sh(2040KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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