It achieves state-of-the-art performance on multiple datasets such as FaceWarehouse, MICC Florence and BU-3DFE. It is fast, accurate, and robust to pose and occlussions. ![]() The method enforces a hybrid-level weakly-supervised training for CNN-based 3D face reconstruction. Tong, Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set, IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) on Analysis and Modeling of Faces and Gestures (AMFG), 2019. This is a tensorflow implementation of the following paper: This repo will not be maintained in future. ***: A PyTorch implementation which has much better performance and is much easier to use is available now. Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
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