人脸检测-- Face R-FCN + Face R-CNN
2017-11-02 09:56
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Detecting Faces Using Region-based Fully Convolutional Networks
本文使用 R-FCN 来进行人脸检测
R-FCN 相对于 Faster R-CNN 主要讲卷积层前移进行共享计算
人脸检测的挑战性:
本文的 contributions:
1) 提出基于R-FCN 的人脸检测防范: Face R-FCN
2)提出一个 novel position-sensitive average pooling 用于综合人脸各个特征信息
3)在 WIDER FACE dataset and FDDB dataset 性能优异
Face R-FCN framework
Position-Sensitive Average Pooling
人脸不同的特征区域具有不同的权重
We believe such assumption that distinct regions on the face have different importance should also hold in face detection
Multi-Scale Training and Testing
multi-scale training and testing strategy to improve performance
采用 On-line Hard Example Mining (OHEM)
4 Experiments
WIDER FACE
FDDB
下面两篇文献都是基于 Faster R-CNN 来进行人脸检测的
Face Detection with the Faster R-CNN
https://arxiv.org/abs/1606.03473
https://github.com/playerkk/face-py-faster-rcnn
Face R-CNN
https://arxiv.org/abs/1706.01061
111
本文使用 R-FCN 来进行人脸检测
R-FCN 相对于 Faster R-CNN 主要讲卷积层前移进行共享计算
人脸检测的挑战性:
本文的 contributions:
1) 提出基于R-FCN 的人脸检测防范: Face R-FCN
2)提出一个 novel position-sensitive average pooling 用于综合人脸各个特征信息
3)在 WIDER FACE dataset and FDDB dataset 性能优异
Face R-FCN framework
Position-Sensitive Average Pooling
人脸不同的特征区域具有不同的权重
We believe such assumption that distinct regions on the face have different importance should also hold in face detection
Multi-Scale Training and Testing
multi-scale training and testing strategy to improve performance
采用 On-line Hard Example Mining (OHEM)
4 Experiments
WIDER FACE
FDDB
下面两篇文献都是基于 Faster R-CNN 来进行人脸检测的
Face Detection with the Faster R-CNN
https://arxiv.org/abs/1606.03473
https://github.com/playerkk/face-py-faster-rcnn
Face R-CNN
https://arxiv.org/abs/1706.01061
111
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