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

About

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.

Yuhan Wang, Xu Chen, Junwei Zhu, Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Yongjian Wu, Feiyue Huang, Rongrong Ji• 2021

Related benchmarks

TaskDatasetResultRank
Face Forgery DetectionDFDC
AUC62.29
25
Face SwappingFFHQ
FID11.58
21
Face SwappingFaceForensics++ (test)
ID Retrieval98.48
17
Face SwappingFaceForensics++
ID Retrieval0.9801
14
Face SwappingFFHQ (test)
FID11.81
13
Face SwappingFace Swapping Evaluation Set (test)
ID Retrieval Top-1 Acc15
8
Face SwappingCelebA (test)
FID12.68
8
Face SwappingMPIE
CSIM0.092
7
Face SwappingFaceForensics++ 10K (test)
ID Consistency98.48
4
Face Forgery DetectionFF++
AUC38.97
4
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