| | --- |
| | 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} |
| | } |
| | ``` |
