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Deep generative models like StyleGAN hold the promise of semantic image editing: modifying images by their content, rather than their pixel values. ... Unfortunately, working with arbitrary images requires inverting the StyleGAN generator, which has remained challenging so far. ... Hypernetworks predict the parameters of other networks  ; for StyleGAN specifically Hyperstyle  and  use them to predict parameters offsets which fine-tune a generator, much like in Pivotal ...arXiv:2205.06304v1 fatcat:lrcvul44pvehrk37mgmo6ng2gu
Combined with StyleGAN's visual quality, these properties gave rise to unparalleled editing capabilities. ... Seeking to bring StyleGAN's latent control to real-world scenarios, the study of GAN inversion and latent space embedding has quickly gained in popularity. ... Images synthesized by StyleGAN, its followups and derivative works. Fig. 2 . 2 Fig. 2. Editing a real image of Scarlett Johansson (on the top left) with StyleGAN. ...arXiv:2202.14020v1 fatcat:qu3plbdnszdujcwxwq3zizysje