LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup

ICCV 2019 Qiao GuGuanzhi WangMang Tik ChiuYu-Wing TaiChi-Keung Tang

We propose a local adversarial disentangling network (LADN) for facial makeup and de-makeup. Central to our method are multiple and overlapping local adversarial discriminators in a content-style disentangling network for achieving local detail transfer between facial images, with the use of asymmetric loss functions for dramatic makeup styles with high-frequency details... (read more)

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