Knowledge Commons of Institute of Automation,CAS
Selective Refinement Network for High Performance Face Detection | |
Chi, Cheng1,2; Zhang, Shifeng2,3![]() ![]() ![]() ![]() | |
2019 | |
会议名称 | Association for the Advancement of Artificial Intelligence |
会议日期 | 2019-02 |
会议地点 | 美国夏威夷 |
摘要 | High performance face detection remains a very challenging problem, especially when there exists many tiny faces. This paper presents a novel single-shot face detector, named Selective Refinement Network (SRN), which introduces novel two-step classification and regression operations selectively into an anchor-based face detector to reduce false positives and improve location accuracy simultaneously. In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module. The STC aims to filter out most simple negative anchors from low level detection layers to reduce the search space for the subsequent classifier, while the STR is designed to coarsely adjust the locations and sizes of anchors from high level detection layers to provide better initialization for the subsequent regressor. Moreover, we design a Receptive Field Enhancement (RFE) block to provide more diverse receptive field, which helps to better capture faces in some extreme poses. As a consequence, the proposed SRN detector achieves state-of-the-art performance on all the widely used face detection benchmarks, including AFW, PASCAL face, FDDB, and WIDER FACE datasets. Codes will be released to facilitate further studies on the face detection problem. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 生物特征识别 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39048 |
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 |
作者单位 | 1.Aerospace Information Research Institute Chinese Academy of Sciences 2.Institute of Automation Chinese Academy of Sciences 3.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Chi, Cheng,Zhang, Shifeng,Xing, Junliang,et al. Selective Refinement Network for High Performance Face Detection[C],2019. |
条目包含的文件 | 条目无相关文件。 |
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