通过潜在空间评估,实现公正的高质量肖像画
Doaa Almhaithawi1, Alessandro Bellini2, Tania Cerquitelli1
1Department of Control and Computer Engineering, Politecnico di Torino, 10129 Torino, Italy.
Journal of imaging
|July 26, 2024
概括
一个人工智能系统DaVinciFace使用潜伏空间探索将用户肖像转化为莱昂纳多·达芬奇风格的图像. 它保留了诸如性别,种族和年龄之类的社会分类,较少的载体对特征的影响更为显著.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 数字艺术 数字艺术 数字艺术
背景情况:
- 潜在的太空探索可以合成像图像这样的复杂数据.
- StyleGAN2是一种强大的生成对抗网络,用于图像合成.
- 莱昂纳多·达芬奇的肖像画经常显示特定的人口统计.
研究的目的:
- 为了介绍DaVinciFace,一个用于生成达芬奇风格肖像的AI系统.
- 调查系统能够保留社会分类 (性别,种族,年龄) 的能力.
- 评估潜空间向量操纵对面部特征的影响.
主要方法:
- 利用了StyleGAN2隐藏空间用于肖像生成.
- 开发了DaVinciFace人工智能系统,用于用户肖像的转换.
- 分析了1158张肖像,操纵了矢量表示.
- 通过众包采购收集人类反以进行评估.
主要成果:
- 达芬奇脸成功地产生了高质量的达芬奇风格的肖像.
- 较少的隐性空间向量对面部特征产生了更大的影响.
- 人类反表明对身份特征损失的耐受性,具有更强的风格影响.
- 关于特征保存的非洲化个体的例外情况.
结论:
- 隐藏空间探索对于风格图像转换是有效的.
- 达芬奇脸展示了人工智能在艺术合成中的实际应用.
- 系统性能在不同的社会分类和风格强度上有所不同.
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