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