README.md

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<div align="center">
<h1 align="center">
  NeuFrameQ: Neural Frame Fields for Scalable and Generalizable Anisotropic Quadrangulation (ICCV 2025)
</h1>
<a href='https://thuliu-yt16.github.io/neuframeq/'><img src='https://img.shields.io/badge/Project%20Page-NeuFrameQ-blue'></a>  <br>

<b>  
<a href="https://github.com/thuliu-yt16" target="_blank">Ying-Tian Liu</a><sup>1</sup>,  
Jiajun Li<sup>3</sup>,  
<a href="#" target="_blank">Yu-Tao Liu</a><sup>2</sup>,  
<a href="https://xinyu-andy.github.io/" target="_blank">Xin Yu</a><sup>4</sup>,  
<a href="https://github.com/bennyguo" target="_blank">Yuan-Chen Guo</a><sup>2</sup>,  
<a href="https://yanpei.me" target="_blank">Yan-Pei Cao</a><sup>2</sup>,  
<a href="https://scholar.google.com/citations?user=Dqjnn0gAAAAJ" target="_blank">Ding Liang</a><sup>2</sup>,  
<a href="https://faculty.runi.ac.il/arik/site/index.asp" target="_blank">Ariel Shamir</a><sup>5</sup>,  
<a href="https://scholar.google.com/citations?user=AWtV-EQAAAAJ" target="_blank">Song-Hai Zhang</a><sup>1</sup>  
</b>  
<br>  
<sup>1</sup>Tsinghua University · <sup>2</sup>VAST · <sup>3</sup>University of Chicago · <sup>4</sup>The University of Hong Kong · <sup>5</sup>Reichman University  
<br>  
</div>  

---

## Introduction

**NeuFrameQ-Dataset** is a large-scale collection of quadrilateral meshes released together with our paper *NeuFrameQ: Neural Frame Fields for Scalable and Generalizable Anisotropic Quadrangulation* (ICCV 2025).

The dataset consists of **279,680 quad meshes** with diverse geometry, intended to support research in quadrangulation, remeshing, geometry processing, and so on. Importantly, the models in NeuFrameQ-Dataset are a subset of Objaverse. The UUIDs are consistent with Objaverse, ensuring easy cross-referencing between datasets.

* **Models**: There are 279,680 meshes stored in `.ply` format, grouped by the first two characters of their UUIDs.
* **Metadata**: Each group of models has a corresponding metadata file (`.json.gz`) located in the `metadata/` directory. The metadata includes license information, UUIDs, and other attributes.

---

## License

Individual meshes are licensed under Creative Commons terms as provided in the metadata. Please consult the metadata files to verify the license of each object.

**License Distribution**:

- [CC BY](https://creativecommons.org/licenses/by/4.0/): 266,419
- [CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/4.0/): 2,088
- [CC BY-SA](https://creativecommons.org/licenses/by-sa/4.0/): 2,445
- [CC BY-NC](https://creativecommons.org/licenses/by-nc/4.0/): 7,858
- [CC0](https://creativecommons.org/publicdomain/zero/1.0/): 870

---

## BibTex

```
@inproceedings{liu2025neuframeq,
  title     = {NeuFrameQ: Neural Frame Fields for Scalable and Generalizable Anisotropic Quadrangulation},
  author    = {Liu, Ying-Tian and Li, Jiajun and Liu, Yu-Tao and Yu, Xin and Guo, Yuan-Chen and Cao, Yan-Pei and Liang, Ding and Shamir, Ariel and Zhang, Song-Hai},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  year      = {2025}
}
```