We propose an e cient 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.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/662516 |
| Date | 14 April 2020 |
| Creators | Abdal, Rameen |
| Contributors | Wonka, Peter, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Hadwiger, Markus, Ghanem, Bernard |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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