计算机科学 ›› 2023, Vol. 50 ›› Issue (2): 221-230.doi: 10.11896/jsjkx.220800166
梁伟亮1, 李悦2, 王棚飞3
LIANG Weiliang1, LI Yue2, WANG Pengfei3
摘要: 人脸生成可以将人脸的样式和头部的姿态进行组合,合成虚假的人脸图像,常用于性别转换、姿势修改等视觉任务。基于GAN的人脸生成方法大幅度提高了人脸生成的质量和可编辑性,但是这些生成方法网络结构复杂、计算资源需求大,很难直接应用于实际场景中。为了实现高效的人脸生成,提出了一种基于TransEditor的轻量化人脸生成方法,并探讨了相应的应用规范路径。在技术层面,首先,以TransEditor人脸编辑网络模型为基础,参考StyleGAN2等轻量化网络模型的生成器结构,设计了轻量化的人脸生成网络模型。其次,从生成损失、对抗损失、重建损失等方面分析了网络模型的损失函数,提出使用PReLU激活函数代替Softplus激活函数来提高生成器的生成效果。最后,大量实验证明,提出的基于TransEditor的轻量化人脸生成方法的LPIPS仅减少了0.0042,大幅度减少了模型的训练时间和参数量,提高了人脸生成模型的运行效率。在应用规范层面,需完善现有的规制措施,规范所提方法的使用,使技术进步更好地服务于社会发展。
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