Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?

Rameen Abdal, Yipeng Qin, Peter Wonka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

43 Scopus citations

Abstract

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 FFHD 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.
Original languageEnglish (US)
Title of host publication2019 IEEE/CVF International Conference on Computer Vision (ICCV)
PublisherIEEE
Pages4431-4440
Number of pages10
ISBN (Print)9781728148038
DOIs
StatePublished - 2019

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