Person Image Generation Guided by Posture, Expression and Illumination

表达式(计算机科学) 计算机视觉 人工智能 图像(数学) 计算机科学 心理学 程序设计语言
作者
Kai Wang,Hong Lu,Jing Guo,Yongzhen Ke,Suohe Yang,Kai Tian
出处
期刊:International Journal of Computational Intelligence and Applications [Imperial College Press]
标识
DOI:10.1142/s146902682450010x
摘要

Person pose transfer has shown great application prospects and potential in recent years. However, this research mainly focuses on posture transfer and does not pay much attention to other human body attributes. In addition, there are problems such as blurred facial expressions and inconsistent facial texture. In order to solve these problems and improve user experience, this paper proposes a multi-feature transfer person image generation model, which combines facial expression transfer and pose transfer and completes the lighting reconstruction of person images. Our model can simultaneously migrate and supplement facial expressions while migrating a person’s posture, ensuring the consistency of characters’ overall migration. Our model can freely switch personal body lighting to adapt to different scenes, greatly improving the user experience. The experimental results show that our method’s preservation rate for face identity is improved by nearly 35% compared with the benchmark, and the similarity index for the overall person body is improved by nearly 14%. The evaluation results indicate that our method performs well in person posture transfer. The experimental results show that the proposed method is superior to the existing algorithms in person posture transformation.

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