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 This is a python implementation of the following paper:
 
-Y. Deng, J. Yang, S. Xu, D. Chen, Y. Jia, and X. Tong. [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://arxiv.org/abs/1903.08527). IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) on Analysis and Modeling of Faces and Gestures (AMFG), 2019. (__Best Paper Award!__)
+Y. Deng, J. Yang, S. Xu, D. Chen, Y. Jia, and X. Tong, [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://arxiv.org/abs/1903.08527), IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) on Analysis and Modeling of Faces and Gestures (AMFG), 2019. (__Best Paper Award!__)
 
 The method enforces a hybrid-level weakly-supervised training to for CNN-based 3D face reconstruction. It is fast, accurate, and robust to pose and occlussions. It achieves state-of-the-art performance on multiple datasets such as FaceWarehouse, MICC Florence and BU-3DFE.