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. Our project page is this https URL
在本文中，我们介绍了Trim 3D高斯喷溅（TrimGS），用于从图像重构精确的3D几何形状。之前在3D高斯用于几何重构的研究主要集中在探索强几何正则化。相比之下，我们提出了一种新颖的视角：通过高斯修剪来获取场景的精确3D几何形状，该方法选择性地移除不准确的几何形状，同时保留准确的结构。为此，我们分析了单个3D高斯的贡献，并提出了一种基于贡献的修剪策略，以移除多余或不准确的高斯。此外，我们的实验和理论分析表明，相对较小的高斯尺度是表示和优化复杂细节中一个不可忽视的因素。因此，提出的TrimGS保持了相对较小的高斯尺度。此外，TrimGS也与以前技术中有效的几何正则化策略兼容。当与原始的3DGS和最新的2DGS结合使用时，TrimGS始终能提供更精确的几何形状和更高的感知质量。