Peak-Piloted Deep Network for Facial Expression Recognition

@article{Zhao2016PeakPilotedDN,
  title={Peak-Piloted Deep Network for Facial Expression Recognition},
  author={Xiangyu Zhao and Xiaodan Liang and Luoqi Liu and Teng Li and Yugang Han and Nuno Vasconcelos and Shuicheng Yan},
  journal={ArXiv},
  year={2016},
  volume={abs/1607.06997}
}
Objective functions for training of deep networks for face-related recognition tasks, such as facial expression recognition (FER), usually consider each sample independently. In this work, we present a novel peak-piloted deep network (PPDN) that uses a sample with peak expression (easy sample) to supervise the intermediate feature responses for a sample of non-peak expression (hard sample) of the same type and from the same subject. The expression evolving process from non-peak expression to… 
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