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Video Style Transfer based on Convolutional Neural Networks

Author

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  • Sun Dong
  • Youdong Ding
  • Yun Qian
  • Mengfan Li
  • Savvas A. Chatzichristofis

Abstract

Video style transfer using convolutional neural networks (CNN), a method from the deep learning (DL) field, is described. The CNN model, the style transfer algorithm, and the video transfer process are presented first; then, the feasibility and validity of the proposed CNN-based video transfer method are estimated in a video style transfer experiment on The Eyes of Van Gogh. The experimental results show that the proposed approach not only yields video style transfer but also effectively eliminates flickering and other secondary problems in video style transfer.

Suggested Citation

  • Sun Dong & Youdong Ding & Yun Qian & Mengfan Li & Savvas A. Chatzichristofis, 2022. "Video Style Transfer based on Convolutional Neural Networks," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, March.
  • Handle: RePEc:hin:jnlmpe:8918722
    DOI: 10.1155/2022/8918722
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