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Peng et al. "RED-Net: A Recurrent Encoder–Decoder Network for Video-Based Face Alignment". IJCV, 2018.

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RED-Net: A Recurrent Encoder–Decoder Network for Video-Based Face Alignment

This is the demo codes for both training and testing in Pytorch.

The Caffe codes and pretrained model is here.

Related publications

"RED-Net: A recurrent encoder-decoder network for video-based face alignment."

Xi Peng , Rogerio S Feris, Xiaoyu Wang, and Dimitris N Metaxas

International Journal of Computer Vision (IJCV), 1-17, 2018. Download PDF


"A Recurrent Encoder-Decoder Network for Sequential Face Alignment."

Xi Peng , Rogerio S Feris, Xiaoyu Wang, and Dimitris N Metaxas

European Conference on Computer Vision (ECCV), Amsterdam, 2016. (Oral) Download PDF, Slides, Poster

Reference

@article{peng2018red,
  title={RED-Net: A Recurrent Encoder--Decoder Network for Video-Based Face Alignment},
  author={Peng, Xi and Feris, Rogerio S and Wang, Xiaoyu and Metaxas, Dimitris N},
  journal={International Journal of Computer Vision},
  pages={1--17},
  year={2018},
  publisher={Springer US}
}
@InProceedings{PengECCV16,
author = "Peng, Xi and Feris, Rogerio S.and Wang, Xiaoyu and Metaxas, Dimitris N.",
title = "A Recurrent Encoder-Decoder Network for Sequential Face Alignment",
booktitle = "European Conference on Computer Vision (ECCV)",
year = "2016",
pages="38--56"}

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Peng et al. "RED-Net: A Recurrent Encoder–Decoder Network for Video-Based Face Alignment". IJCV, 2018.

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