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Overparameterization Improves StyleGAN Inversion [article]

Yohan Poirier-Ginter, Alexandre Lessard, Ryan Smith, Jean-François Lalonde
2022 arXiv   pre-print
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 [20] ; for StyleGAN specifically Hyperstyle [5] and [13] use them to predict parameters offsets which fine-tune a generator, much like in Pivotal  ... 
arXiv:2205.06304v1 fatcat:lrcvul44pvehrk37mgmo6ng2gu

State-of-the-Art in the Architecture, Methods and Applications of StyleGAN [article]

Amit H. Bermano and Rinon Gal and Yuval Alaluf and Ron Mokady and Yotam Nitzan and Omer Tov and Or Patashnik and Daniel Cohen-Or
2022 arXiv   pre-print
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