Update README.md

README.md

@@ -5,4 +5,33 @@ language:
 pretty_name: ModelNet_Splats
 size_categories:
 - 10B<n<100B
----
+---
+
+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](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 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}, 
+}
+```