“Parsing-conditioned Anime Translation: A New Dataset and Method” by Li, Xu, Zhao, Zhou, Liu, et al. …

  • ©Zhansheng Li, Yangyang Xu, Nanxuan Zhao, Yang Zhou, Yongtuo Liu, and Shengfeng He




    Parsing-conditioned Anime Translation: A New Dataset and Method

Session/Category Title: Image and Video Editing




    The abstract art of anime presents a challenging misaligned image translation problem. We propose a new anime translation framework that leverages prior knowledge of a pre-trained StyleGAN model. The proposed framework incorporates disentangled encoders, four tailored losses, and a FaceBank aggregation method to generate in-domain animes. We further introduce the Danbooru-Parsing dataset, which connects face semantics with appearances, enabling constrained translation settings. Experiments demonstrate editability and extend the method to manga images. We produce the first feasible solution to anime translation.

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