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In this work, we propose a high fidelity face swapping method, calledHifiFace, which can well preserve the face shape of the source face andgenerate photo-realistic results. Unlike other existing face swapping worksthat only use face recognition model to keep the identity similarity, wepropose 3D shape-aware identity to control the face shape with the geometricsupervision from 3DMM and 3D face reconstruction method. Meanwhile, weintroduce the Semantic Facial Fusion module to optimize the combination ofencoder and decoder features and make adaptive blending, which makes theresults more photo-realistic. Extensive experiments on faces in the wilddemonstrate that our method can preserve better identity, especially on theface shape, and can generate more photo-realistic results than previousstate-of-the-art methods.

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