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We propose Image2StyleGAN++, a flexible image editing framework with manyapplications. Our framework extends the recent Image2StyleGAN in three ways.First, we introduce noise optimization as a complement to the $W^+$ latentspace embedding. Our noise optimization can restore high-frequency features inimages and thus significantly improves the quality of reconstructed images,e.g. a big increase of PSNR from 20 dB to 45 dB. Second, we extend the global$W^+$ latent space embedding to enable local embeddings. Third, we combineembedding with activation tensor manipulation to perform high-quality localedits along with global semantic edits on images. Such edits motivate varioushigh-quality image editing applications, e.g. image reconstruction, imageinpainting, image crossover, local style transfer, image editing usingscribbles, and attribute level feature transfer. Examples of the edited imagesare shown across the paper for visual inspection.

Image2StyleGAN++: How to Edit the Embedded Images?