TL;DR: We propose SplineGS, a COLMAP-free dynamic 3D Gaussian Splatting (3DGS) framework for high-quality reconstruction and fast rendering from monocular videos. At its core is a novel Motion-Adaptive Spline (MAS) method, which represents continuous dynamic 3D Gaussian trajectories using cubic Hermite splines. Experiments show that SplineGS significantly outperforms state-of-the-art methods in novel view synthesis quality for dynamic scenes from monocular videos, achieving thousands times faster rendering speed.
Overview of SplineGS. Our SplineGS leverages spline-based functions to model the deformation of dynamic 3D Gaussians with a novel Motion-Adaptive Spline (MAS) architecture. It is composed of sets of learnable control points based on a cubic Hermite spline function to accurately model the trajectory of each dynamic 3D Gaussian and to achieve faster rendering speed. To avoid any preprocessing of camera parameters, i.e. COLMAP-free, we adopt a two-stage optimization: warm-up and main training stages.
@InProceedings{Park_2025_CVPR,
author = {Park, Jongmin and Bui, Minh-Quan Viet and Bello, Juan Luis Gonzalez and Moon, Jaeho and Oh, Jihyong and Kim, Munchurl},
title = {SplineGS: Robust Motion-Adaptive Spline for Real-Time Dynamic 3D Gaussians from Monocular Video},
booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
month = {June},
year = {2025},
pages = {26866-26875}
}