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Reconstruction Network for single-face detection and landmark localization

机译:用于人脸检测和地标定位的重建网络

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摘要

This paper introduces Reconstruction Network to reconstruct the regions of interest of one or more objects within an optical image without time-consuming image segmentation or key-point descriptors calculation. We evaluate Reconstruction Network using face detection and facial landmark localization. Experiments show that new algorithm learns the structure of face and facial landmarks automatically and obtains state-of-the-art performance for face detection (almost 50% higher detection rates than widely used method) and facial land-mark localization (0.03 lower mean error of key point location than two recently published methods) while requiring only a fraction of the computing resources.
机译:本文介绍了重建网络,可在不耗时的图像分割或关键点描述符计算的情况下重建光学图像中一个或多个对象的关注区域。我们使用脸部检测和脸部界标定位评估重建网络。实验表明,该新算法可自动学习人脸和人脸地标的结构,并获得最新的人脸检测性能(比广泛使用的方法高出近50%的检测率)和人脸地标定位(平均误差低0.03)关键点位置的数量要比最近发布的两种方法要少),而只需要计算资源的一小部分。

著录项

  • 来源
    《Optical and quantum electronics》 |2017年第8期|282.1-282.9|共9页
  • 作者

    Bo Yu; Ian Lane; Fang Chen;

  • 作者单位

    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China,Carnegie Mellon University, NASA Research Park #23, Moffett Field, CA 94043, USA;

    Carnegie Mellon University, NASA Research Park #23, Moffett Field, CA 94043, USA;

    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China,University of Chinese Academy of Sciences, Beijing 100049, China,Hainan Key Laboratory of Earth Observation, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Sanya 572029, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Reconstruction Network; Face detection; Landmark detection;

    机译:重建网络;人脸检测地标检测;

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