High-resolution face swapping via latent semantics disentanglement

• Main Authors: XU, Yangyang, DENG, Bailin, WANG, Junle, JING, Yanqing, PAN, Jia, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Image and video synthesis and generation; Face and gestures; Low-level vision; Computer vision; Codes; Face recognition; Semantics; Generators; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• 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
• Institution: Singapore Management University

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...