DreamGaussian4D：生成式4D高斯飞溅

DreamGaussian4D: Generative 4D Gaussian Splatting

December 28, 2023

作者: Jiawei Ren, Liang Pan, Jiaxiang Tang, Chi Zhang, Ang Cao, Gang Zeng, Ziwei Liu

cs.AI

摘要

最近在4D内容生成领域取得了显著进展。然而，现有方法存在优化时间长、缺乏运动可控性和细节水平低的问题。在本文中，我们介绍了DreamGaussian4D，这是一个高效的4D生成框架，基于4D高斯飞溅表示法。我们的关键洞察是，在高斯飞溅中对空间变换进行明确建模，使其相对于隐式表示更适合于4D生成设置。DreamGaussian4D将优化时间从几个小时减少到几分钟，允许灵活控制生成的3D运动，并产生可在3D引擎中高效渲染的动画网格。

English

Remarkable progress has been made in 4D content generation recently. However, existing methods suffer from long optimization time, lack of motion controllability, and a low level of detail. In this paper, we introduce DreamGaussian4D, an efficient 4D generation framework that builds on 4D Gaussian Splatting representation. Our key insight is that the explicit modeling of spatial transformations in Gaussian Splatting makes it more suitable for the 4D generation setting compared with implicit representations. DreamGaussian4D reduces the optimization time from several hours to just a few minutes, allows flexible control of the generated 3D motion, and produces animated meshes that can be efficiently rendered in 3D engines.