Compact 3D Gaussian Splatting For Dense Visual SLAM

Understand

Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes.

• However, these approaches are built on a tremendous number of redundant 3D Gaussian ellipsoids, leading to high memory and storage costs, and slow training speed.
• To address the limitation, we propose a compact 3D Gaussian Splatting SLAM system that reduces the number and the parameter size of Gaussian ellipsoids.
• A sliding window-based masking strategy is first proposed to reduce the redundant ellipsoids.