pith. sign in

arxiv: 2403.11247 · v3 · pith:HYNSITQOnew · submitted 2024-03-17 · 💻 cs.CV · cs.RO

Compact 3D Gaussian Splatting For Dense Visual SLAM

Tianchen Deng , Chang Nie , Shuhong Liu , Wenhua Wu , Jianfei Yang , Shenghai Yuan , Jiuming Liu , Danwei Wang
show 1 more author
Hesheng Wang
This is my paper
classification 💻 cs.CV cs.RO
keywords gaussianellipsoidsslamaccuratecompactestimationgeometrymethod
0
0 comments X
read the original abstract

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. Then we observe that the covariance matrix (geometry) of most 3D Gaussian ellipsoids are extremely similar, which motivates a novel geometry codebook to compress 3D Gaussian geometric attributes, i.e., the parameters. Robust and accurate pose estimation is achieved by a global bundle adjustment method with reprojection loss. Extensive experiments demonstrate that our method achieves faster training and rendering speed while maintaining the state-of-the-art (SOTA) quality of the scene representation.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Mamba-VGGT: Persistent Long-Sequence Video Geometry Grounded Transformer via External Sliding Window Mamba Memory

    cs.CV 2026-05 unverdicted novelty 7.0

    Mamba-VGGT introduces a Sliding Window Mamba memory module and Zero-Init Spatial Memory Injector to enable persistent long-range geometric reasoning in VGGT for extended video sequences.

  2. DINO-VO: Learning Where to Focus for Enhanced State Estimation

    cs.CV 2026-04 unverdicted novelty 6.0

    DINO-VO achieves state-of-the-art monocular visual odometry accuracy and generalization by training a differentiable patch selector together with multi-task features and inverse-depth bundle adjustment.

  3. VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction

    cs.CV 2026-05 unverdicted novelty 5.0

    VGGT-Occ embeds geometric tokens via PA-DA and uses sequential coarse-to-fine gated fusion to reach 33.00% IoU and 21.08% mIoU on SurroundOcc-nuScenes while using only ~41M parameters in the occupancy head.

  4. The Code Whisperer: LLM and Graph-Based AI for Smell and Vulnerability Resolution

    cs.SE 2026-04 unverdicted novelty 5.0

    A hybrid graph-plus-LLM framework improves detection and repair of code smells and vulnerabilities over graph-only or LLM-only baselines on multi-language datasets.