HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping
Yuhan Wang1,2* Xu Chen1,3* Junwei Zhu1 Wenqing Chu1 Ying Tai1† Chengjie Wang1 Jilin Li1 Yongjian Wu1 Feiyue Huang1 Rongrong Ji3,4
1Youtu Lab, Tencent 2Zhejiang University 3Media Analytics and Computing Lab, Department of Artificial Intelligence, School of Informatics, Xiamen University 4Institute of Artificial Intelligence, Xiamen University
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 wild faces 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.
