Learning to Avoid Errors in GANs by Manipulating Input Spaces

3 Jul 2017Alexander B. Jung

Despite recent advances, large scale visual artifacts are still a common occurrence in images generated by GANs. Previous work has focused on improving the generator's capability to accurately imitate the data distribution $p_{data}$... (read more)

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