High-resolution face swapping via latent semantics disentanglement
We present a novel high-resolution face swapping method using the inherent prior knowledge of a pre-trained GAN model. Although previous research can leverage generative priors to produce high-resolution results, their quality can suffer from the entangled semantics of the latent space. We explicitl...
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Main Authors: | , , , , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2022
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Online Access: | https://ink.library.smu.edu.sg/sis_research/8532 https://ink.library.smu.edu.sg/context/sis_research/article/9535/viewcontent/Xu_High_Resolution_Face_Swapping_via_Latent_Semantics_Disentanglement_CVPR_2022_paper.pdf |
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Institution: | Singapore Management University |
Language: | English |