| 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. | |
| 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} | |
| } | |
| ``` |