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OperaGAN: A simultaneous transfer network for opera makeup and complex headwear.

Yue Ma1, Chunjie Xu2, Wei Song2

  • 1School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450000, China; Henan Academy of Big Data, Zhengzhou University, Zhengzhou 450000, China.

Neural Networks : the Official Journal of the International Neural Network Society
|December 15, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces OperaGAN, a novel network for transferring Peking Opera makeup and headwear styles to portraits. The method effectively handles complex details, ensuring accurate makeup and headwear transfer simultaneously.

Keywords:
Generative adversarial networksLocal discriminatorsMakeup transferOpera makeup and headwear

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Digital Art

Background:

  • Traditional makeup transfer methods primarily focus on facial features, often neglecting headwear details.
  • Simultaneous transfer of complex facial and headwear makeup in portraits remains a significant challenge.

Purpose of the Study:

  • To develop a robust makeup transfer network capable of handling both facial and headwear elements in Peking Opera portraits.
  • To address the limitations of existing techniques in capturing intricate texture details of headwear.

Main Methods:

  • Construction of a dedicated Peking Opera makeup dataset.
  • Proposal of the OperaGAN network, featuring a Makeup and Headwear Style Encoder (MHSEnc) and an Identity Coding and Makeup Fusion (ICMF) module.
  • Utilization of multiple overlapping local discriminators for high-frequency detail transfer.

Main Results:

  • Achieved state-of-the-art performance in simultaneously transferring Peking Opera facial makeup and headwear styles.
  • Demonstrated the capability to transfer headwear with missing components and control makeup intensity.
  • Successfully transferred high-frequency details characteristic of opera makeup.

Conclusions:

  • OperaGAN offers a significant advancement in portrait style transfer, particularly for culturally rich domains like Peking Opera.
  • The proposed method effectively addresses the challenge of simultaneous facial and headwear makeup transfer, preserving intricate details.
  • The developed network provides controllable and accurate style transfer for complex artistic representations.