English

DAS3R: Dynamics-Aware Gaussian Splatting for Static Scene Reconstruction

Computer Vision and Pattern Recognition 2024-12-30 v1

Abstract

We propose a novel framework for scene decomposition and static background reconstruction from everyday videos. By integrating the trained motion masks and modeling the static scene as Gaussian splats with dynamics-aware optimization, our method achieves more accurate background reconstruction results than previous works. Our proposed method is termed DAS3R, an abbreviation for Dynamics-Aware Gaussian Splatting for Static Scene Reconstruction. Compared to existing methods, DAS3R is more robust in complex motion scenarios, capable of handling videos where dynamic objects occupy a significant portion of the scene, and does not require camera pose inputs or point cloud data from SLAM-based methods. We compared DAS3R against recent distractor-free approaches on the DAVIS and Sintel datasets; DAS3R demonstrates enhanced performance and robustness with a margin of more than 2 dB in PSNR. The project's webpage can be accessed via \url{https://kai422.github.io/DAS3R/}

Keywords

Cite

@article{arxiv.2412.19584,
  title  = {DAS3R: Dynamics-Aware Gaussian Splatting for Static Scene Reconstruction},
  author = {Kai Xu and Tze Ho Elden Tse and Jizong Peng and Angela Yao},
  journal= {arXiv preprint arXiv:2412.19584},
  year   = {2024}
}
R2 v1 2026-06-28T20:49:48.248Z