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Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
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We propose an efficient algorithm to embed a given image into the latent space of StyleGAN. This embedding enables semantic image editing operations that can be applied to existing photographs. Taking the StyleGAN trained on the FFHQ dataset as an example, we show results for image morphing, style transfer, and expression transfer. Studying the results of the embedding algorithm provides valuable insights into the structure of the StyleGAN latent space. We propose a set of experiments to test what class of images can be embedded, how they are embedded, what latent space is suitable for embedding, and if the embedding is semantically meaningful.
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Cited by 1 Pith paper
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StyleAutoEncoder for manipulating image attributes using pre-trained StyleGAN
StyleAE is a lightweight autoencoder attached to StyleGAN that edits image attributes by modifying single coordinates of a learned target latent space, matching or approaching flow-based baselines with far lower cost.
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