| --- |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| pretty_name: ModelNet_Splats |
| size_categories: |
| - 10B<n<100B |
| extra_gated_prompt: | |
| If you find our method/dataset helpful, please consider citing our paper: |
| |
| @inproceedings{ma2025large, |
| title={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}, |
| booktitle={2025 International Conference on 3DV}, |
| pages={145--155}, |
| year={2025}, |
| organization={IEEE} |
| } |
| --- |
| |
| This repository contains ShapeSplat, 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](DATA.md) for details about the data. |
| |
| If you use the ModelNet_Splats data, you agree to abide by the [ModelNet terms of use](https://modelnet.cs.princeton.edu/#). 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 find the data helpful, please consider citing the ShapeSplat paper. |
| ``` |
| @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} |
| } |
| |
| @article{chang2015shapenet, |
| title={Shapenet: An information-rich 3d model repository}, |
| author={Chang, Angel X and Funkhouser, Thomas and Guibas, Leonidas and Hanrahan, Pat and Huang, Qixing and Li, Zimo and Savarese, Silvio and Savva, Manolis and Song, Shuran and Su, Hao and others}, |
| journal={arXiv preprint arXiv:1512.03012}, |
| year={2015} |
| } |
| ``` |
