This repository contains ShapeSplats, a large dataset of Gaussian splats spanning 65K objects in 87 unique categories (gathered from ShapeNetCore, ShapeNet-Part, and ModelNet).

ModelNet_Splats consists of the 12 objects across 40 categories of ModelNet40.

The data is distributed as ply files where information about each Gaussian is encoded in custom vertex attributes. Please see DATA.md for details about the data.

If you use the ModelNet_Splats data, you agree to abide by the ModelNet terms of use. You are only allowed to redistribute the data to your research associates and colleagues provided that they first agree to be bound by these terms and conditions.

If you use this data, please cite the ShapeSplat paper along with main ShapeNet technical report.

@article{ma2024shapesplat,
  title={ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining},
  author={Ma, Qi and Li, Yue and Ren, Bin and Sebe, Nicu and Konukoglu, Ender and Gevers, Theo and Van Gool, Luc and Paudel, Danda Pani},
  journal={arXiv preprint arXiv:2408.10906},
  year={2024}
}

@misc{wu20153dshapenetsdeeprepresentation,
      title={3D ShapeNets: A Deep Representation for Volumetric Shapes}, 
      author={Zhirong Wu and Shuran Song and Aditya Khosla and Fisher Yu and Linguang Zhang and Xiaoou Tang and Jianxiong Xiao},
      year={2015},
      eprint={1406.5670},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1406.5670}, 
}