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This paper introduces MaskFaceGAN, a novel approach to face attribute editing capable of generating high-resolution, artefact-free and photo-realistic editing results through a carefully designed optimization procedure applied over the StyleGAN2 latent space. The presented ($1024\times 1024$) examples show editing results for four target attributes. Best viewed zoomed-in.

DOI