LoG

zju3dv活跃维护

用高斯层级表示做三维重建和新视角合成，能从多视角图像重建可实时渲染的场景，适合需要高质量渲染的 3D 视觉任务。

Level of Gaussians

暂无版本770star42fork同步于 2026-11-07 07:30 UTC

三维重建高斯泼溅新视角合成实时渲染场景表示

对比 GitHub 官网 3d-reconstruction gaussian-splatting novel-view-synthesis

怎么上手

由 README 提炼，执行前请确认

原文

python3 apps/train.py --cfg config/example/test/train.yml split train

硬件要求按 README 说明

README 明确说明使用单张 RTX 4090 进行训练和实时渲染；是否支持其他 GPU 型号及 CPU 运行未说明。

下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼

没人工点评？写下你的经验

用单张 RTX 4090 训练并实时渲染城市级高斯泼溅场景

用高斯层级表示做三维重建和新视角合成，能从多视角图像重建可实时渲染的场景，适合需要高质量渲染的 3D 视觉任务。

核心能力

基于高斯泼溅技术重建城市级大场景
单卡 RTX 4090 即可完成训练与实时渲染
按数据集规模自动配置启发式训练参数
提供插值可视化并输出 rgb.mp4 视频
用 Colmap 预处理数据，附最小示例数据集

容易踩的坑

安装需按 docs/install.md 单独配置，依赖 PyTorch 与 diff-gaussian-rasterization；数据集需先用 Colmap 按 docs/preprocess.md 预处理；实时渲染工具 README 称后续更新，当前尚未提供。

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

用户点评

登录用户的真实使用记录，可按版本和硬件筛选

共 0 条

还没有人点评。第一个说出真实体验的人最有价值。

README 原文

未翻译

在 GitHub 打开

python star

LoG utilizes a single RTX 4090 for training highly realistic urban-scale models and for their real-time rendering. Visit our project page for more demos.

https://github.com/chingswy/LoGvideos/assets/22812405/abb200c1-5b9c-48fd-a9a1-f235499153d2

Our code is built upon PyTorch and leverages gaussian-splatting techniques.

Quick Start

For a smooth setup, follow the installation guide.

Dataset Preparation

We employ Colmap to prepare the dataset. Refer to the preprocessing documentation for detailed instructions. A minimal example dataset is provided here.

Training

Training the model is as simple as one command:

python3 apps/train.py --cfg config/example/test/train.yml split train

We automatically configure heuristic parameters based on the dataset size.

We provide a path for interpolation visualization

python3 apps/train.py --cfg config/example/test/train.yml split demo_interpolate ckptname output/example/test/level_of_gaussian/model_init.pth

The visualization video will be stored at output/example/test/level_of_gaussian/demo_interpolate/rgb.mp4

Immersive Visualization :rocket:

We will update a real-time rendering tool designed for immersive visualization.

Acknowledgements

We acknowledge the following inspirational prior work:

The rendering GUI is powered by our EasyVolcap tool.

Contributions are warmly welcomed! If you've made significant progress on any of these fronts, please consider submitting a pull request.

Citation

If you find this code useful for your research, please cite us using the following BibTeX entry.

@inproceedings{shuai2024LoG,
  title={Real-Time View Synthesis for Large Scenes with Millions of Square Meters},
  author={Shuai, Qing and Guo, Haoyu and Xu, Zhen and Lin, Haotong and Peng, Sida and Bao, Hujun and Zhou, Xiaowei},
  year={2024}
}