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Add dataset card for ARSG-110K (#1)

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- Add dataset card for ARSG-110K (780ec715ee5cb26acc68dc47cc2dc8ae0ad1a047)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

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- ---
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- license: apache-2.0
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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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+ ---
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+
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+ # ARSG-110K
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+
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+ 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).
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+
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+ - **Project Page:** [https://zx-yin.github.io/3dfixer](https://zx-yin.github.io/3dfixer)
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+ - **Github Repository:** [https://github.com/HorizonRobotics/3D-Fixer](https://github.com/HorizonRobotics/3D-Fixer)
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+ - **Paper:** [https://arxiv.org/abs/2604.04406](https://arxiv.org/abs/2604.04406)
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+
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+ ## Dataset Summary
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+
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+ 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:
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+ - Over **110,000** diverse scenes.
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+ - **3 million** annotated images.
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+ - High-fidelity 3D ground truth, including object-level layouts and annotations.
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+ - Built upon the [TRELLIS-500K](https://github.com/microsoft/TRELLIS/blob/main/DATASET.md) dataset.
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+
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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.
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+
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+ ## Citation
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+
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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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+ ```