Face Relighting
Identity preserving face relighting using GAN
Identity preserving face relighting using GAN
People
Kyungmin Kim and Hyunjung Shim
Abstract
Identity preserving is a challenging problem of face image generation using GAN.
Realistic synthesis of relighting face image is one way to augment low-shot data.
Physical-based intrinsic image disentangling approach induce semantic separation of latent variables.
Overview
