通过几何对齐实现实时数据高效的肖像造型
Xinrui Wang1, Zhuoru Li2, Xuanyu Yin3
1The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 110-0033, Japan.
概括
本研究介绍了一种新的肖像风格化方法,在生成对抗网络 (GAN) 中使用可微分的薄板间隙 (TPS) 模块. 这种方法增强了几何一致性,并在移动设备上实现实时造型.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 图像处理 图像处理
背景情况:
- 现有的肖像风格化方法与几何一致性和特征分布差异作斗争.
- 这些局限性阻碍了由于计算限制而在稀有风格和移动设备上的应用.
研究的目的:
- 开发一种新的肖像风格化技术,确保几何一致性并提高风格化质量.
- 创建一个高效,轻量级的模型,适合在移动设备上实时推断.
主要方法:
- 将可微分的薄板间隙 (TPS) 模块集成到一个端到端的生成对抗网络 (GAN) 框架中.
- 在像素和特征空间中利用面部地标在全球和本地尺度上进行几何对齐.
主要成果:
- 与现有方法相比,实现了卓越的忠实性和风格一致性.
- 训练数据的效率提高了2倍,计算复杂度降低了100倍.
- 在移动设备上以512x512分辨率启用实时推断 (30 FPS).
结论:
- 拟议的TPS集成的GAN框架有效地解决了肖像风格化的几何不一致性.
- 这种轻量级模型提供了一个实用的解决方案,用于在资源有限的设备上高质量,实时的肖像风格化.
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