---
license: apache-2.0
task_categories:
- image-to-3d
tags:
- 3d
- scene-generation
- cvpr
---

# ARSG-110K

[**Project Page**](https://zx-yin.github.io/3dfixer/) | [**Paper**](https://huggingface.co/papers/2604.04406) | [**GitHub**](https://github.com/HorizonRobotics/3D-Fixer)

ARSG-110K is a large-scale scene-level dataset comprising over 110K diverse scenes and 3M annotated images with high-fidelity 3D ground truth. It is designed to support the training and evaluation of compositional 3D scene generation and in-place completion models. The dataset provides accurate 3D object-level ground-truth, layout, and annotations.

This dataset was introduced as part of the paper: **3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image**.

## Dataset Details

- **Source Data**: The `Objaverse_github.csv` and `ObjaverseXL_sketchfab.csv` are subsets of those from [TRELLIS-500K](https://github.com/microsoft/TRELLIS?tab=readme-ov-file#-dataset).
- **Assets**: The `hdrs.zip`, `materials_floor.zip`, and `materials_wall.zip` contain assets from [BlenderKit](https://www.blenderkit.com/).
- **Examples**: This repository provides renderings of 1000 example scenes.

## Accessing the Data

Please follow the [detailed instructions](https://github.com/HorizonRobotics/3D-Fixer/blob/main/DATASET.md) on the official GitHub repository to access the full dataset beyond the example renderings.

## 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}
}
```