OperaGAN: A simultaneous transfer network for opera makeup and complex headwear.
Journal:
Neural networks : the official journal of the International Neural Network Society
PMID:
39675095
Abstract
Standard makeup transfer techniques mainly focus on facial makeup. The texture details of headwear in style examples tend to be ignored. When dealing with complex portrait style transfer, simultaneous correct headwear and facial makeup transfer often cannot be guaranteed. In this paper, we construct the Peking Opera makeup dataset and propose a makeup transfer network for Opera faces called OperaGAN. This network consists of two key components: the Makeup and Headwear Style Encoder module (MHSEnc) and the Identity Coding and Makeup Fusion module (ICMF). MHSEnc is specifically designed to extract the style features from global and local perspectives. ICMF extracts the source image's facial features and combines them with the style features to generate the final transfer result. In addition, multiple overlapping local discriminators are utilized to transfer the high-frequency details in opera makeup. Experiments demonstrate that our method achieves state-of-the-art results in simultaneously transferring opera makeup and headwear. And the method can transfer headwear with missing content and controllable intensity makeup. The code and dataset will be available at https://github.com/Ivychun/OperaGAN.