End-To-end cascade cnn for simultaneously face detection and alignment

Sanyuan Zhao*, Hongmei Song, Weilin Cong, Qi Qi, Hui Tian

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Real-world face detection and alignment demand an advanced discriminative model to address challenges by pose, lighting and expression. Recent studies have utilized the relation between face detection and alignment to make models computationally efficiency, but they ignore the connection between each cascade CNNs. In this paper, we combine detection, calibration and alignment in each cascade structure and propose an End-To-End cascade Online Hard Example Mining (OHEM) for training, which expert in accelerating convergence. Experiments on FDDB and AFLW demonstrate considerable improvement on accuracy and speed.

源语言英语
主期刊名Proceedings - 2017 International Conference on Virtual Reality and Visualization, ICVRV 2017
出版商Institute of Electrical and Electronics Engineers Inc.
35-40
页数6
ISBN(电子版)9781538626368
DOI
出版状态已出版 - 2 7月 2017
活动7th International Conference on Virtual Reality and Visualization, ICVRV 2017 - Zhengzhou, 中国
期限: 21 10月 201722 10月 2017

出版系列

姓名Proceedings - 2017 International Conference on Virtual Reality and Visualization, ICVRV 2017

会议

会议7th International Conference on Virtual Reality and Visualization, ICVRV 2017
国家/地区中国
Zhengzhou
时期21/10/1722/10/17

指纹

探究 'End-To-end cascade cnn for simultaneously face detection and alignment' 的科研主题。它们共同构成独一无二的指纹。

引用此

Zhao, S., Song, H., Cong, W., Qi, Q., & Tian, H. (2017). End-To-end cascade cnn for simultaneously face detection and alignment. 在 Proceedings - 2017 International Conference on Virtual Reality and Visualization, ICVRV 2017 (页码 35-40). 文章 8719201 (Proceedings - 2017 International Conference on Virtual Reality and Visualization, ICVRV 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICVRV.2017.00016