D3T-GAN: Data-Dependent Domain Transfer GANs for Few-shot Image Generation. (arXiv:2205.06032v1 [cs.CV])

Web: http://arxiv.org/abs/2205.06032

As an important and challenging problem, few-shot image generation aims at
generating realistic images through training a GAN model given few samples. A
typical solution for few-shot generation is to transfer a well-trained GAN
model from a data-rich source domain to the data-deficient target domain. In
this paper, we propose a novel self-supervised transfer scheme termed D3T-GAN,
addressing the cross-domain GANs transfer in few-shot image generation.
Specifically, we design two individual strategies to transfer knowledge between
generators and discriminators, respectively. …

arxiv cv data gan gans image image generation transfer