CVPR2025
DashGaussian: Optimizing 3D Gaussian Splatting in 200 Seconds
Youyu Chen, Junjun Jiang, Kui Jiang, Xiao Tang, Zhihao Li, Xianming Liu, Yinyu Nie
Abstract
Figure 1. We propose DashGaussian, a fast 3D Gaussian Splatting (3DGS) optimization method that can be easily plugged into existing 3DGS backbones. DashGaussian significantly boosts the training speed of various 3DGS backbones by 45.7% on average without trading off rendering quality. Equipping DashGaussian to prior-art 3DGS methods, we reduce the optimization time of a 3DGS model with millions of primitives to 200 seconds on a consumer-grade GPU. The figures above show the scene "stump" in the Mip-NeRF 360 dataset.