Add metadata and improve dataset card for ARSG-110K
Browse filesHi! I'm Niels, part of the community science team at Hugging Face. I've updated the dataset card for ARSG-110K to include relevant metadata, such as task categories and license, and added links to the paper, project page, and code repository. I've also included the BibTeX citation to help researchers properly credit your work. This will make the dataset more discoverable and useful for the community!
README.md
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license: apache-2.0
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---
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---
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license: apache-2.0
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task_categories:
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- image-to-3d
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tags:
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- 3d
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- scene-generation
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- cvpr
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---
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# ARSG-110K
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[**Project Page**](https://zx-yin.github.io/3dfixer/) | [**Paper**](https://huggingface.co/papers/2604.04406) | [**GitHub**](https://github.com/HorizonRobotics/3D-Fixer)
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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.
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This dataset was introduced as part of the paper: **3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image**.
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## Dataset Details
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- **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).
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- **Assets**: The `hdrs.zip`, `materials_floor.zip`, and `materials_wall.zip` contain assets from [BlenderKit](https://www.blenderkit.com/).
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- **Examples**: This repository provides renderings of 1000 example scenes.
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## Accessing the Data
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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.
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## Citation
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```bibtex
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@inproceedings{yin2026tdfixer,
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title={3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image},
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author={Yin, Ze-Xin and Liu, Liu and Wang, Xinjie and Sui, Wei and Su, Zhizhong and Yang, Jian and Xie, jin},
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booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
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year={2026}
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}
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```
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