| --- |
| license: apache-2.0 |
| task_categories: |
| - image-to-3d |
| --- |
| |
| # ARSG-110K |
|
|
| ARSG-110K is a large-scale scene-level dataset for 3D scene generation and completion, introduced in the paper [3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image](https://huggingface.co/papers/2604.04406). |
|
|
| - **Project Page:** [https://zx-yin.github.io/3dfixer](https://zx-yin.github.io/3dfixer) |
| - **Github Repository:** [https://github.com/HorizonRobotics/3D-Fixer](https://github.com/HorizonRobotics/3D-Fixer) |
| - **Paper:** [https://arxiv.org/abs/2604.04406](https://arxiv.org/abs/2604.04406) |
|
|
| ## Dataset Summary |
|
|
| ARSG-110K is designed to address the data scarcity bottleneck in compositional 3D scene generation. It is one of the largest scene-level datasets to date, comprising: |
| - Over **110,000** diverse scenes. |
| - **3 million** annotated images. |
| - High-fidelity 3D ground truth, including object-level layouts and annotations. |
| - Built upon the [TRELLIS-500K](https://github.com/microsoft/TRELLIS/blob/main/DATASET.md) dataset. |
|
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| The dataset supports tasks such as in-place completion, where complete 3D assets are generated conditioned on partially visible point clouds cropped from fragmented geometry. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{yin2026tdfixer, |
| title={3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image}, |
| author={Yin, Ze-Xin and Liu, Liu and Wang, Xinjie and Sui, Wei and Su, Zhizhong and Yang, Jian and Xie, jin}, |
| booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference}, |
| year={2026} |
| } |
| ``` |
