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.ipynb_checkpoints/README-checkpoint.md

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----
-pretty_name: LoBE-GS Dataset
-license: other
-tags:
-  - 3d-gaussian-splatting
-  - 3d-reconstruction
-  - novel-view-synthesis
-  - large-scale-scenes
----
-
-# 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](https://github.com/Sunnyhong0326/lobe-gs)
-- [Project Page](https://sunnyhong0326.github.io/lobe-gs)
-- [Paper](https://arxiv.org/abs/2510.01767)
-## 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:
-
-```bash
-hf download Sunnyhong0326/LoBE-GS-Dataset \
-    --repo-type dataset \
-    --local-dir ./datasets
-```
-
-Download only the original-pose configuration:
-
-```bash
-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}
-}
-```