language:
- en
size_categories:
- 10K<n<100K
ArXiv:
- https://arxiv.org/abs/2504.11218
In this repository, we present 3DAffordSplat, the first large-scale, multi-modal dataset tailored for 3DGS-based affordance reasoning. This dataset includes 23k Gaussian instances, 8k point cloud instances, and 6k manually annotated affordance labels, encompassing 21 object categories and 18 affordance types.
Dataset Structure
After downloading, the data structure should be as follows:
—Seen
├── train
│ ├── bag
│ │ ├── Gaussian
│ │ │ └── GS_0017.ply
│ │ │ ......
│ │ ├── PointCloud
│ │ │ └── PC_0001.ply
│ │ │ ......
│ │ ├── contain
│ │ │ ├── GS_anno_0017.ply
│ │ │ ├── PC_anno_0001.json
│ │ │ ......
│ │ └── grasp
│ │ ......
│ └── bed
│ ......
│
├── val
│ ├── bag
│ │ ├── Gaussian
│ │ │ └── GS_0009.ply
│ │ │ ......
│ │ ├── contain
│ │ │ └── GS_anno_0009.ply
│ │ │ ......
│ │ └── grasp
│ │ ......
│ └── bed
│ ......
│
└── test
├── bag
│ ├── Gaussian
│ │ └── GS_0001.ply
│ │ ......
│ ├── contain
│ │ └── GS_anno_0001.ply
│ │ ......
│ └── grasp
│ ......
└── bed
......
—Affordance-Question.csv
—obj_aff_structure.json
—UnSeen_test.json
—UnSeen_train.json
Dataset Details
For more information on detailed statistics and the methodology of AffordSplat, please refer to the following resources:
- Repository: Github Repository
- Paper: 3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians
Additionally, we sincerely thank Guantian Liu, Yao Xiao, Xinyu Li, Kecheng Liang and Yipeng Ouyang for their contributions.
Contact
This project is for research purpose only, please contact us for the licence of commercial use. For any other questions please contact ([email protected], [email protected] or [email protected]).
Citation
If you use this data, please cite our paper.
@misc{wei20253daffordsplatefficientaffordancereasoning,
title={3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians},
author={Zeming wei and Junyi Lin and Yang Liu and Weixing Chen and Jingzhou Luo and Guanbin Li and Liang Lin},
year={2025},
eprint={2504.11218},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2504.11218},
}
Acknowledgement
The construction of AffordSplat dataset is based on 3DAffordanceNet, LASO and ShapeSplat. We sincerely thank them for their contributions to the community.