Temporally Coherent Video Harmonization Using Adversarial Networks

@article{Huang2020TemporallyCV,
  title={Temporally Coherent Video Harmonization Using Adversarial Networks},
  author={Haozhi Huang and Senzhe Xu and Junxiong Cai and Wei Liu and Shimin Hu},
  journal={IEEE Transactions on Image Processing},
  year={2020},
  volume={29},
  pages={214-224}
}
  • Haozhi Huang, Senzhe Xu, +2 authors Shimin Hu
  • Published 2020
  • Computer Science, Medicine, Mathematics
  • IEEE Transactions on Image Processing
  • Compositing is one of the most important editing operations for images and videos. The process of improving the realism of composite results is often called harmonization. Previous approaches for harmonization mainly focus on images. In this paper, we take one step further to attack the problem of video harmonization. Specifically, we train a convolutional neural network in an adversarial way, exploiting a pixel-wise disharmony discriminator to achieve more realistic harmonized results and… CONTINUE READING

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