README.md

CityGaussian Series for High-quality Large-Scale Scene Reconstruction with Gaussians

Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences

This repo contains official implementations of our series of work in large-scale scene reconstruction with Gaussian Splatting, Star ⭐ us if you like it!

• CityGaussianV2: Efficient and Geometrically Accurate Reconstruction for Large-Scale Scenes
• CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians (ECCV 2024)

The links above points to the papers. Users could follow the instruction to download COLMAP results, checkpoints, and try the V1 of our CityGaussian. The code of V2 is also coming soon.

📰 News

[2024.11.04] Announcement of our CityGaussianV2!

[2024.10.12] Checkpoints on main datasets have been released!

[2024.10.11] Updates FAQ! If you are stucked, please first check whether it can solves the problem.

[2024.08.20] Updates Custom Dataset Instructions!

[2024.08.05] Our code is now available! Welcome to try it out!

[2024.07.18] Camera Ready version now can be accessed through arXiv. More insights are included.

📝 TODO List

• Release the V2 of CityGaussian.
• Release code and checkpoints of CityGaussian.
• Release ColMap results of main datasets.

📄 License

This work is under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

🤗 Citation

If you find this repository useful, please use the following BibTeX entry for citation.

@misc{liu2024citygaussianv2efficientgeometricallyaccurate,
      title={CityGaussianV2: Efficient and Geometrically Accurate Reconstruction for Large-Scale Scenes}, 
      author={Yang Liu and Chuanchen Luo and Zhongkai Mao and Junran Peng and Zhaoxiang Zhang},
      year={2024},
      eprint={2411.00771},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2411.00771}, 
}

@inproceedings{liu2025citygaussian,
  title={Citygaussian: Real-time high-quality large-scale scene rendering with gaussians},
  author={Liu, Yang and Luo, Chuanchen and Fan, Lue and Wang, Naiyan and Peng, Junran and Zhang, Zhaoxiang},
  booktitle={European Conference on Computer Vision},
  pages={265--282},
  year={2025},
  organization={Springer}
}

👏 Acknowledgements

This repo benefits from 3DGS, LightGaussian, Gaussian Lightning. Thanks for their great work!