From Facial Parts Responses to Face Detection: A Deep Learning Approach

@article{Yang2015FromFP,
  title={From Facial Parts Responses to Face Detection: A Deep Learning Approach},
  author={Shuo Yang and Ping Luo and Chen Change Loy and Xiaoou Tang},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={3676-3684}
}
In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding performance on FDDB, PASCAL Face, and AFW. Specifically, our method achieves a high recall rate of 90.99% on the challenging FDDB benchmark, outperforming the state-of-the-art method [23] by a large margin of 2.91%. Importantly, we consider finding faces from a new perspective through scoring facial parts responses by their spatial structure and arrangement. The scoring mechanism is carefully formulated… CONTINUE READING
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