【文件属性】:
文件名称:腾讯人脸识别论文
文件大小:4.25MB
文件格式:PDF
更新时间:2021-01-15 06:27:47
人脸识别 腾讯
Face detection has achieved great success using the region-based methods. In
this report, we propose a region-based face detector applying deep networks in
a fully convolutional fashion, named Face R-FCN. Based on Region-based Fully
Convolutional Networks (R-FCN), our face detector is more accurate and computationally
efficient compared with the previous R-CNN based face detectors.
In our approach, we adopt the fully convolutional Residual Network (ResNet) as
the backbone network. Particularly, we exploit several new techniques including
position-sensitive average pooling, multi-scale training and testing and on-line
hard example mining strategy to improve the detection accuracy. Over two most
popular and challenging face detection benchmarks, FDDB and WIDER FACE,
Face R-FCN achieves superior performance over state-of-the-arts.