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- W4286770111 abstract "Despite recent advances in semantic manipulation using StyleGAN, semantic editing of real faces remains challenging. The gap between the $W$ space and the $W$+ space demands an undesirable trade-off between reconstruction quality and editing quality. To solve this problem, we propose to expand the latent space by replacing fully-connected layers in the StyleGAN's mapping network with attention-based transformers. This simple and effective technique integrates the aforementioned two spaces and transforms them into one new latent space called $W$++. Our modified StyleGAN maintains the state-of-the-art generation quality of the original StyleGAN with moderately better diversity. But more importantly, the proposed $W$++ space achieves superior performance in both reconstruction quality and editing quality. Despite these significant advantages, our $W$++ space supports existing inversion algorithms and editing methods with only negligible modifications thanks to its structural similarity with the $W/W$+ space. Extensive experiments on the FFHQ dataset prove that our proposed $W$++ space is evidently more preferable than the previous $W/W$+ space for real face editing. The code is publicly available for research purposes at https://github.com/AnonSubm2021/TransStyleGAN." @default.
- W4286770111 created "2022-07-23" @default.
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- W4286770111 date "2021-05-29" @default.
- W4286770111 modified "2023-09-25" @default.
- W4286770111 title "Transforming the Latent Space of StyleGAN for Real Face Editing" @default.
- W4286770111 doi "https://doi.org/10.48550/arxiv.2105.14230" @default.
- W4286770111 hasPublicationYear "2021" @default.
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