Creating high-quality 3D avatars using 3D Gaussian Splatting (3DGS) from a monocular video benefits virtual reality and telecommunication applications. However, existing automatic methods exhibit artifacts under novel poses due to limited information in the input video. We propose AvatarPerfect, a novel system that allows users to iteratively refine 3DGS avatars by manually editing the rendered avatar images. In each iteration, our system suggests a new body and camera pose to help users identify and correct artifacts. The edited images are then used to update the current avatar, and our system suggests the next body and camera pose for further refinement. To investigate the effectiveness of AvatarPerfect, we conducted a user study comparing our method to an existing 3DGS editor SuperSplat, which allows direct manipulation of Gaussians without automatic pose suggestions. The results indicate that our system enables users to obtain higher quality refined 3DGS avatars than the existing 3DGS editor.
利用3D高斯点绘（3D Gaussian Splatting, 3DGS）从单目视频创建高质量3D角色，为虚拟现实和远程通信应用提供了重要支持。然而，由于输入视频信息有限，现有自动化方法在生成新姿态时往往会出现伪影问题。我们提出了一种新系统 AvatarPerfect，允许用户通过手动编辑渲染的角色图像，迭代地优化3DGS角色。 在每次迭代中，系统会建议新的身体和相机姿态，帮助用户识别并修正伪影。用户编辑后的图像用于更新当前角色模型，随后系统继续推荐下一个身体和相机姿态，进行进一步优化。为评估 AvatarPerfect 的有效性，我们与现有的3DGS编辑器 SuperSplat 进行了对比研究。后者允许直接操控高斯点，但缺乏自动姿态推荐功能。研究结果表明，与现有编辑器相比，我们的系统能够帮助用户生成质量更高的3DGS角色模型。