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Hierarchical Semantic Regularization of Latent Spaces in StyleGANs
[article]
2022
arXiv
pre-print
Progress in GANs has enabled the generation of high-resolution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such images via mathematical operations on the latent style vectors in the W/W+ space that effectively modulate the rich hierarchical representations of the generator. Such operations have recently been generalized beyond mere attribute swapping in the original StyleGAN paper to include interpolations. In spite of many significant
arXiv:2208.03764v1
fatcat:ni6mauhaojckldawnqmzg4alzy