Invertible Conditional GAN Revisited: Photo-to-Manga Face Translation with Modern Architectures (Student Abstract)
DOI:
https://doi.org/10.1609/aaai.v37i13.26972Keywords:
GAN, Manga, GAN Inversion, Image-to-Image TranslationAbstract
Recent style translation methods have extended their transferability from texture to geometry. However, performing translation while preserving image content when there is a significant style difference is still an open problem. To overcome this problem, we propose Invertible Conditional Fast GAN (IcFGAN) based on GAN inversion and cFGAN. It allows for unpaired photo-to-manga face translation. Experimental results show that our method could translate styles under significant style gaps, while the state-of-the-art methods could hardly preserve image content.Downloads
Published
2023-09-06
How to Cite
Hatakeyama, T., Saito, R., Hiruta, K., Hashimoto, A., & Kurihara, S. (2023). Invertible Conditional GAN Revisited: Photo-to-Manga Face Translation with Modern Architectures (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16224-16225. https://doi.org/10.1609/aaai.v37i13.26972
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Section
AAAI Student Abstract and Poster Program