Image2StyleGAN++: how to edit the embedded images?

Abdal, Rameen, Qin, Yipeng ORCID: https://orcid.org/0000-0002-1551-9126 and Wonka, Peter 2020. Image2StyleGAN++: how to edit the embedded images? Presented at: Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, Washington, USA, 16-18 June 2020. Item availability restricted.

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Abstract

We propose Image2StyleGAN++, a flexible image editing framework with many applications. Our framework extends the recent Image2StyleGAN [1] in three ways. First, we introduce noise optimization as a complement to the W+ latent space embedding. Our noise optimization can restore high frequency features in images and thus significantly improves the quality of reconstructed images, e.g. a big increaseofPSNRfrom20dBto45dB.Second,we extend the global W+ latent space embedding to enable local embeddings. Third, we combine embedding with activation tensor manipulation to perform high quality local edits along with global semantic edits on images. Such edits motivate various high quality image editing applications, e.g. image reconstruction, image inpainting, image crossover, local style transfer, image editing using scribbles, and attribute level feature transfer. Examples of the edited images are shown across the paper for visual inspection.

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Computer Science & Informatics
Date of First Compliant Deposit:	24 April 2020
Date of Acceptance:	27 February 2020
Last Modified:	07 Nov 2022 10:07
URI:	https://orca.cardiff.ac.uk/id/eprint/131207

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