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[!IMPORTANT]\n\u003e 🌟 Stay up to date at [opendrivelab.com](https://opendrivelab.com/#news)!\n\n\u003cdiv align=\"center\"\u003e\n\n# **MTGS: Multi-Traversal Gaussian Splatting**\n\n[![Arxiv](https://img.shields.io/badge/arXiv-2503.12552-b31b1b.svg?style=for-the-badge\u0026logo=arxiv)](https://arxiv.org/abs/2503.12552)\n[![dataset](https://img.shields.io/badge/HF-Dataset-yellow?style=for-the-badge\u0026logo=huggingface)](https://huggingface.co/datasets/OpenDriveLab/MTGS)\n[![PyTorch](https://img.shields.io/badge/PyTorch-2.0.1-EE4C2C.svg?style=for-the-badge\u0026logo=pytorch)](https://pytorch.org)\n[![Python](https://img.shields.io/badge/python-3.9-blue?style=for-the-badge)](https://www.python.org)\n\n\u003c/div\u003e\n\n\u003cdiv id=\"top\" align=\"center\"\u003e\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/figure_teaser.png\" width=\"1000px\" \u003e\n\u003c/p\u003e\n\u003c/div\u003e\n\n\u003e  Joint effort by Shanghai Innovation Institute (SII) and OpenDriveLab at The University of Hong Kong.\n\n## 🔥 Highlights\n\n- **MTGS** leverages **multi-traversal** data for scene reconstruction with better geometry.\n- 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).\n- We integrate a **web viewer** from nerfstudio to visualize the reconstructed scene and switch nodes between different traversals.\n- [Getting started](docs/install.md) with our codebase now! 🚀\n\n\u003cdiv align=\"center\"\u003e\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/figure_pipeline.png\" width=\"1000px\" \u003e\n\u003c/p\u003e\n\u003c/div\u003e\n\n## 🎬 Video Demos\n\nAll the videos below are reconstructed and rendered with our method, MTGS, from `road_block-331220_4690660_331190_4690710`.\n\n\u003cdiv align=\"center\"\u003e\n\n**Rendered results on training traversals 1, 2, and 3, from top to bottom.**\n\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/road_block-331220_4690660_331190_4690710/traversal_1_trimmed.gif\" width=\"1000px\" \u003e\u003cbr\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/road_block-331220_4690660_331190_4690710/traversal_2_trimmed.gif\" width=\"1000px\" \u003e\u003cbr\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/road_block-331220_4690660_331190_4690710/traversal_3_trimmed.gif\" width=\"1000px\" \u003e\n\n***Novel-view*** results on the testing traversal.\n\n\u003cimg src=\"https://raw.githubusercontent.com/OpenDriveLab/opendrivelab.github.io/refs/heads/master/MTGS/road_block-331220_4690660_331190_4690710/traversal_test_trimmed.gif\" width=\"1000px\" \u003e\n\n\u003c/div\u003e\n\n## 📢 News\n\n- **[2025/05/29]** We release the checkpoints. [Check it out](docs/running.md#optional-download-the-checkpoints)!\n- **[2025/05/27]** Official code release.\n- **[2025/05/14]** Video demo release.\n- **[2025/03/16]** We released our [paper](https://arxiv.org/abs/2503.12552) on arXiv. \n\n## 📋 TODO List\n\n- [x] Official code release.\n- [x] Release the checkpoints.\n- [ ] Demo page.\n\n## 🕹️ Getting Started\n\n- 📦 [Installation](docs/install.md)\n- 📊 [Prepare Data](docs/prepare_dataset.md)\n- 🚀 [Running](docs/running.md)\n\n## ⭐ Citation\n\nIf any parts of our paper and code help your research, please consider citing us and giving a star to our repository.\n\n```bibtex\n@article{li2025mtgs,\n  title={MTGS: Multi-Traversal Gaussian Splatting},\n  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},\n  journal={arXiv preprint arXiv:2503.12552},\n  year={2025}\n}\n```\n\n## ⚖️ License\n\nAll content in this repository is under the [Apache-2.0 license](https://www.apache.org/licenses/LICENSE-2.0).\nThe 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.\n\n## ❤️ Related resources\n\nWe acknowledge all the open-source contributors for the following projects to make this work possible:\n\n- [nerfstudio](https://github.com/nerfstudio-project/nerfstudio)\n- [gsplat](https://github.com/nerfstudio-project/gsplat)\n- [drivestudio](https://github.com/ziyc/drivestudio)\n- [kiss-icp](https://github.com/PRBonn/kiss-icp)\n- [UniDepth](https://github.com/lpiccinelli-eth/UniDepth)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopendrivelab%2Fmtgs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopendrivelab%2Fmtgs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopendrivelab%2Fmtgs/lists"}