--- language: - en size_categories: - 10K 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](https://github.com/HCPLab-SYSU/3DAffordSplat) - **Paper:** [3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians](https://arxiv.org/abs/2504.11218) 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 (weizm6@mail2.sysu.edu.cn, linjy279@mail2.sysu.edu.cn or liuy856@mail.sysu.edu.cn). # 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](https://github.com/Gorilla-Lab-SCUT/AffordanceNet), [LASO](https://github.com/yl3800/laso) and [ShapeSplat](https://huggingface.co/datasets/ShapeSplats/ModelNet_Splats). We sincerely thank them for their contributions to the community.