Corpus ID: 202539084

An Acceleration Framework for High Resolution Image Synthesis

@article{Liu2019AnAF,
  title={An Acceleration Framework for High Resolution Image Synthesis},
  author={Jinlin Liu and Yuan Yao and Jianqiang Ren},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.03611}
}
Synthesis of high resolution images using Generative Adversarial Networks (GANs) is challenging, which usually requires numbers of high-end graphic cards with large memory and long time of training. In this paper, we propose a two-stage framework to accelerate the training process of synthesizing high resolution images. High resolution images are first transformed to small codes via the trained encoder and decoder networks. The code in latent space is times smaller than the original high… Expand
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