StyleRes: Transforming the Residuals for Real Image Editing with StyleGAN
StyleRes: Transforming the Residuals for Real Image Editing with StyleGAN
We present a novel image inversion framework and a training pipeline to achieve high-fidelity image inversion with high-quality attribute editing. Inverting real images into StyleGAN's latent space is an extensively studied problem, yet the trade-off between the image reconstruction fidelity and image editing quality remains an open challenge. The low-rate …