HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

Author:

Wang Yuhan12,Chen Xu13,Zhu Junwei1,Chu Wenqing1,Tai Ying1,Wang Chengjie1,Li Jilin1,Wu Yongjian1,Huang Feiyue1,Ji Rongrong34

Affiliation:

1. Youtu Lab, Tencent

2. Zhejiang University

3. Media Analytics and Computing Lab, Department of Artificial Intelligence, School of Informatics, Xiamen University

4. Institute of Artificial Intelligence, Xiamen University

Abstract

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results. Unlike other existing face swapping works that only use face recognition model to keep the identity similarity, we propose 3D shape-aware identity to control the face shape with the geometric supervision from 3DMM and 3D face reconstruction method. Meanwhile, we introduce the Semantic Facial Fusion module to optimize the combination of encoder and decoder features and make adaptive blending, which makes the results more photo-realistic. Extensive experiments on faces in the wild demonstrate that our method can preserve better identity, especially on the face shape, and can generate more photo-realistic results than previous state-of-the-art methods. Code is available at: https://johann.wang/HifiFace

Publisher

International Joint Conferences on Artificial Intelligence Organization

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