We propose StarGAN v2, a single framework that tackles both and shows significantly improved results over the baselines. Experiments on CelebA-HQ and a new animal faces dataset (AFHQ) validate our superiority in terms of visual quality, diversity, and scalability. To better assess image-to-image translation models, we release AFHQ, high-quality animal faces with large inter- and intra-domain differences.

2020: Yunjey Choi, Youngjung Uh, Jaejun Yoo, Jung-Woo Ha

Keywords: Scalability, Experiment

https://arxiv.org/pdf/1912.01865v2.pdf