In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly focus on exploring strong geometry regularization. Instead, from a fresh perspective, we propose to obtain accurate 3D geometry of a scene by Gaussian trimming, which selectively removes the inaccurate geometry while preserving accurate structures. To achieve this, we analyze the contributions of individual 3D Gaussians and propose a contribution-based trimming strategy to remove the redundant or inaccurate Gaussians. Furthermore, our experimental and theoretical analyses reveal that a relatively small Gaussian scale is a non-negligible factor in representing and optimizing the intricate details. Therefore the proposed TrimGS maintains relatively small Gaussian scales. In addition, TrimGS is also compatible with the effective geometry regularization strategies in previous arts. When combined with the original 3DGS and the state-of-the-art 2DGS, TrimGS consistently yields more accurate geometry and higher perceptual quality.
Trim3DGS can reconstruct smoother normal maps than 3DGS.
Compared with 2DGS, our Trim2DGS exhibits better geometric details and perceptual quality.
Our Trim2DGS significantly enhances perceptual quality in high-frequency regions and substantially reduces the storage consumption.
Our Trim2DGS yields a more uniform distribution of Gaussians while reducing the storage consumption.
For better visualization, we zoom in the details, revealing that Trim2DGS and Trim3DGS exhibit accurate geometry representation.
Our Trim2DGS and Trim3DGS yield a more uniform distribution of Gaussians, representing the geometry more accurately.
@article{fan2024trim,
author = {Fan, Lue and Yang, Yuxue and Li, Minxing and Li, Hongsheng and Zhang, Zhaoxiang},
title = {Trim 3D Gaussian Splatting for Accurate Geometry Representation},
journal = {arXiv preprint arXiv:2406.07499},
year = {2024},
}