https://github.com/opendrivelab/mtgs

MTGS: Multi-Traversal Gaussian Splatting
https://github.com/opendrivelab/mtgs

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MTGS: Multi-Traversal Gaussian Splatting

• Host: GitHub
• URL: https://github.com/opendrivelab/mtgs
• Owner: OpenDriveLab
• License: apache-2.0
• Created: 2025-03-27T03:57:01.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2025-08-21T03:33:58.000Z (5 months ago)
• Last Synced: 2025-10-03T08:47:45.193Z (4 months ago)
• Language: Python
• Homepage:
• Size: 400 KB
• Stars: 94
• Watchers: 6
• Forks: 5
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml

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README

          
> [!IMPORTANT]

> 🌟 Stay up to date at [opendrivelab.com](https://opendrivelab.com/#news)!



# **MTGS: Multi-Traversal Gaussian Splatting**

[![Arxiv](https://img.shields.io/badge/arXiv-2503.12552-b31b1b.svg?style=for-the-badge&logo=arxiv)](https://arxiv.org/abs/2503.12552)

[![dataset](https://img.shields.io/badge/HF-Dataset-yellow?style=for-the-badge&logo=huggingface)](https://huggingface.co/datasets/OpenDriveLab/MTGS)

[![PyTorch](https://img.shields.io/badge/PyTorch-2.0.1-EE4C2C.svg?style=for-the-badge&logo=pytorch)](https://pytorch.org)

[![Python](https://img.shields.io/badge/python-3.9-blue?style=for-the-badge)](https://www.python.org)













>  Joint effort by Shanghai Innovation Institute (SII) and OpenDriveLab at The University of Hong Kong.

## 🔥 Highlights

- **MTGS** leverages **multi-traversal** data for scene reconstruction with better geometry.

- We conduct a robust pipeline to calibrate and reconstruct the [nuPlan](https://www.nuscenes.org/nuplan) dataset with multi-traversal data, which is widely used in the autonomous driving community. See downstream applications in [NAVSIM v2](https://github.com/autonomousvision/navsim).

- We integrate a **web viewer** from nerfstudio to visualize the reconstructed scene and switch nodes between different traversals.

- [Getting started](docs/install.md) with our codebase now! 🚀











## 🎬 Video Demos

All the videos below are reconstructed and rendered with our method, MTGS, from `road_block-331220_4690660_331190_4690710`.



**Rendered results on training traversals 1, 2, and 3, from top to bottom.**









***Novel-view*** results on the testing traversal.





## 📢 News

- **[2025/05/29]** We release the checkpoints. [Check it out](docs/running.md#optional-download-the-checkpoints)!

- **[2025/05/27]** Official code release.

- **[2025/05/14]** Video demo release.

- **[2025/03/16]** We released our [paper](https://arxiv.org/abs/2503.12552) on arXiv. 

## 📋 TODO List

- [x] Official code release.

- [x] Release the checkpoints.

- [ ] Demo page.

## 🕹️ Getting Started

- 📦 [Installation](docs/install.md)

- 📊 [Prepare Data](docs/prepare_dataset.md)

- 🚀 [Running](docs/running.md)

## ⭐ Citation

If any parts of our paper and code help your research, please consider citing us and giving a star to our repository.

```bibtex

@article{li2025mtgs,

  title={MTGS: Multi-Traversal Gaussian Splatting},

  author={Li, Tianyu and Qiu, Yihang and Wu, Zhenhua and Lindstr{\"o}m, Carl and Su, Peng and Nie{\ss}ner, Matthias and Li, Hongyang},

  journal={arXiv preprint arXiv:2503.12552},

  year={2025}

}

```

## ⚖️ License

All content in this repository is under the [Apache-2.0 license](https://www.apache.org/licenses/LICENSE-2.0).

The released data is based on [nuPlan](https://www.nuscenes.org/nuplan) and are under the [CC-BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license.

## ❤️ Related resources

We acknowledge all the open-source contributors for the following projects to make this work possible:

- [nerfstudio](https://github.com/nerfstudio-project/nerfstudio)

- [gsplat](https://github.com/nerfstudio-project/gsplat)

- [drivestudio](https://github.com/ziyc/drivestudio)

- [kiss-icp](https://github.com/PRBonn/kiss-icp)

- [UniDepth](https://github.com/lpiccinelli-eth/UniDepth)