本文介绍了VIVE3D，一种新颖的方法将基于图像的3D GAN的能力扩展到视频编辑，并能以保持身份和时间一致的方式表示输入视频。本文提出了两个新的构建块。首先，通过联合嵌入多个帧并优化相机参数引入了一种新颖的GAN反演技术，专门针对3D GAN。其次，除了传统的语义面部编辑（例如年龄和表情），本文是第一个展示了利用3D GAN的固有属性和本文的光流引导合成技术来组合头部和背景视频，从而实现头部新视角编辑的。本文的实验表明，VIVE3D从各种摄像机角度生成高保真度的面部编辑，并以时间和空间一致的方式与原始视频组合。
标题：VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANs
作者：Anna Frühstück , Nikolaos Sarafianos ,Yuanlu Xu , Peter Wonka and Tony Tung
论文：https://papers.labml.ai/api/v1/redirect/pdf?paper_key=94cfe9fecdd211edb95839eec3084ddd
项目：http://afruehstueck.github.io/vive3D/
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