Corpus ID: 216080860

Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer

@article{Xia2020JointBL,
  title={Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer},
  author={Xide Xia and Meng Zhang and Tianfan Xue and Zheng Sun and Hui Fang and Brian Kulis and Jiawen Chen},
  journal={ArXiv},
  year={2020},
  volume={abs/2004.10955}
}
  • Xide Xia, Meng Zhang, +4 authors Jiawen Chen
  • Published 2020
  • Computer Science
  • ArXiv
  • Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera. Recent approaches, based on deep neural networks, produce impressive results but are either too slow to run at practical resolutions, or still contain objectionable artifacts. We propose a new end-to-end model for photorealistic style transfer that is both fast and inherently generates photorealistic results. The core of our… CONTINUE READING

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