文章链接是:SuGaR:表面对齐高斯展开,实现高效的 3D 网格重建和高质量网格渲染 |IEEE 会议出版物 |IEEE Xplore 实际上就是:SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering这个文章的。这个是用来讲3DGS生成的结果转变成mesh的,转变完成之后就可以进行...
[CV] SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering O网页链接 提出一种方法从3D高斯模糊表征中快速且精确地提取三角网格。首先提出一个正则化项,使高斯分布更好地对齐于场景表面,这样从高斯中提取网格就更容易了。然后提出了一种利用深度图高效采样...
Consequently, the current implementation contains a version of the original3D Gaussian Splatting code, and we built our model as a wrapper of a vanilla 3D Gaussian Splatting model. Please note that, even though this wrapper implementation is convenient for many reasons, it may not be the most ...
Recent advancements in 3D Gaussian Splatting (3DGS), which lead to high-quality novel view synthesis and accelerated rendering, have remarkably improved the quality of radiance field reconstruction. However, the extraction of mesh from a massive number of minute 3D Gaussian points remains great ...
Paper tables with annotated results for SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian Splatting. Gaussian Splatting has recently become very popular as ... A Guédon,V Lepetit - IEEE...
We introduce GSrec, which aims to design a surface-aligned Gaussian Splatting and benefits the surface reconstruction. Key idea: Monocular geometry guidance to augment 3DGS with normal attributes, then use neural implicit representation to joint optimize the moving least square field formed by the ...
最近,3D Gaussian Splatting(3D-GS) 在新视图场景合成中越来越受欢迎。 它解决了与神经辐射场 (NeRF) 相关的训练时间长和渲染速度慢的挑战。 通过快速、可微分的 3D 高斯光栅化,3D-GS实现了实时渲染和加速训练。 然而,它们需要大量的内存资源用于训练和存储,因为它们在每个场景的点云表示中需要数百万个高斯。
$$\begin{aligned} \begin{array}{l} {f_{{\mathrm{length,}}i1i2}} = {\left( {\left\| {p_{i2}^t - p_{i1}^t} \right\| - \left\| {p_{i2}^0 - p_{i1}^0} \right\| } \right) ^2}\\ {f_{{\mathrm{angle,}}i1i2}} = {\mathop {\mathrm{acos}}\nolimits }...
[CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering anttwo.github.io/sugar/ Topics mesh surface-reconstruction mesh-generation nerf neural-rendering gaussian-splatting cvpr2024 3d-gaussian-splatting...