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DAWSON: A Domain Adaptive Few Shot Generation Framework
[article]
2020
arXiv
pre-print
Training a Generative Adversarial Networks (GAN) for a new domain from scratch requires an enormous amount of training data and days of training time. To this end, we propose DAWSON, a Domain Adaptive FewShot Generation FrameworkFor GANs based on meta-learning. A major challenge of applying meta-learning GANs is to obtain gradients for the generator from evaluating it on development sets due to the likelihood-free nature of GANs. To address this challenge, we propose an alternative GAN training
arXiv:2001.00576v1
fatcat:wjud4apyubdlzohgmiaw5qb4mm