SunnyHung/LoBE-GS-dataset

LoBE-GS Dataset

This repository provides the preprocessed datasets used in LoBE-GS: Load-Balanced and Efficient 3D Gaussian Splatting for Large-Scale Scene Reconstruction.

Resources

• GitHub Repository
• Project Page
• Paper

Dataset Organization

The datasets are organized into two configurations:

• original-poses/: Datasets with original camera parameters, used in the main paper and supplementary experiments except Supplementary Material Section G.
• refined-poses/: Datasets with COLMAP-re-estimated camera parameters, used in Supplementary Section G for camera pose re-estimation and appearance modeling experiments.

The experiments cover scenes from MatrixCity, Mill19, and UrbanScene3D.

Download

Download the entire dataset:

hf download Sunnyhong0326/LoBE-GS-Dataset \
    --repo-type dataset \
    --local-dir ./datasets

Download only the original-pose configuration:

hf download Sunnyhong0326/LoBE-GS-Dataset \
    --repo-type dataset \
    --include "original-poses/**" \
    --local-dir ./datasets

For refined poses, replace original-poses with refined-poses.

Citation

If you use these datasets in your research, please cite the original dataset papers and our LoBE-GS paper.

@inproceedings{li2023matrixcity,
  title={MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond},
  author={Li, Yixuan and Jiang, Lihan and Xu, Linning and Xiangli, Yuanbo and Wang, Zhenzhi and Lin, Dahua and Dai, Bo},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={3205--3215},
  year={2023}
}

@inproceedings{UrbanScene3D,
title={Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset},
author={Liqiang Lin and Yilin Liu and Yue Hu and Xingguang Yan and Ke Xie and Hui Huang},
booktitle={ECCV},
pages = {93--109},
year={2022},
}

@InProceedings{Turki_2022_CVPR,
    author    = {Turki, Haithem and Ramanan, Deva and Satyanarayanan, Mahadev},
    title     = {Mega-NERF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2022},
    pages     = {12922-12931}
}