most citedSLGAN: Style- and Latent-guided Generative Adversarial Network for Desirable Makeup Transfer and Removal

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CV2020★ 2 cited

SLGAN: Style- and Latent-guided Generative Adversarial Network for Desirable Makeup Transfer and Removal

Daichi Horita, Kiyoharu Aizawa

There are five features to consider when using generative adversarial networks to apply makeup to photos of the human face. These features include (1) facial components, (2) intera…