MOST-Net: A Memory Oriented Style Transfer Network for Face Sketch Synthesis

@article{Ji2022MOSTNetAM,
  title={MOST-Net: A Memory Oriented Style Transfer Network for Face Sketch Synthesis},
  author={Fan Ji and Muyi Sun and Xingqun Qi and Qi Li and Zhenan Sun},
  journal={2022 26th International Conference on Pattern Recognition (ICPR)},
  year={2022},
  pages={733-739}
}
  • Fan JiMuyi Sun Zhenan Sun
  • Published 8 February 2022
  • Computer Science
  • 2022 26th International Conference on Pattern Recognition (ICPR)
Face sketch synthesis has been widely used in multimedia entertainment and law enforcement. Despite the recent developments in deep neural networks, accurate and realistic face sketch synthesis is still a challenging task due to the diversity and complexity of human faces. Current image-to-image translation-based face sketch synthesis frequently encounters over-fitting problems when it comes to small-scale datasets. To tackle this problem, we present an end-to-end Memory Oriented Style Transfer… 

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