FaceScape provides large-scale high-quality 3D face datasets, parametric models, docs and toolkits about 3D face related technology. [CVPR2020 paper] [extended arXiv Report] [supplementary]
Our latest progress will be updated to this repository constantly - [latest update: 2023/10/20]
The data can be downloaded at https://facescape.nju.edu.cn/ after requesting a license key.
New: Share link on Google Drive is available after requesting the license key, view here for detail.
New: The bilinear model ver1.6 can be downloaded without requesting a license key, view here for the link and rules.
The available sources include:
Item (Docs) | Description | Quantity | Quality |
---|---|---|---|
TU models | Topologically uniformed 3D face models with displacement map and texture map. |
16940 models (847 id × 20 exp) |
Detailed geometry, 4K dp/tex maps |
Multi-view data | Multi-view images, camera parameters and corresponding 3D face mesh. |
>400k images (359 id × 20 exp × ≈60 view) |
4M~12M pixels |
Bilinear model | The statistical model to transform the base shape into the vector space. |
4 for different settings | Only for base shape. |
Info list | Gender / age of the subjects. | 847 subjects | -- |
The datasets are only released for non-commercial research use. As facial data involves the privacy of participants, we use strict license terms to ensure that the dataset is not abused.
We present a benchmark to evaluate the accuracy of single-view face 3D reconstruction (SVFR) methods, view here for the details.
Start using python toolkit here, the demos include:
High-fidelity 3D Face Generation from Natural Language Descriptions (CVPR 2023)
Menghua Wu, Hao Zhu#, Linjia Huang, Yiyu Zhuang, Yuanxun Lu, Xun Cao
RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs (AAAI 2023)
Longwei Guo, Hao Zhu#, Yuanxun Lu, Menghua Wu, Xun Cao
Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation (ECCV2022)
Jingwang Ling, Zhibo Wang, Ming Lu, Quan Wang, Chen Qian, Feng Xu
HeadNeRF: A Real-Time NeRF-Based Parametric Head Model (CVPR2022)
Yang Hong, Bo Peng, Haiyao Xiao, Ligang Liu, Juyong Zhang
ImFace: A Nonlinear 3D Morphable Face Model with Implicit Neural Representations (CVPR2022)
Mingwu Zheng, Hongyu Yang, Di Huang, Liming Chen
Detailed Facial Geometry Recovery from Multi-view Images by Learning an Implicit Function (AAAI 2022)
Yunze Xiao*, Hao Zhu*, Haotian Yang, Zhengyu Diao, Xiangju Lu, Xun Cao
Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment (ACM MM 2021)
Yuxing Wang, Yawen Lu, Zhihua Xie, Guoyu Lu
Detailed Riggable 3D face Prediction Code of FaceScape (CVPR2020)
Haotian Yang*, Hao Zhu*, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao
If you find this project helpful to your research, please consider citing:
@article{zhu2023facescape,
title={FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction},
author={Zhu, Hao and Yang, Haotian and Guo, Longwei and Zhang, Yidi and Wang, Yanru and Huang, Mingkai and Wu, Menghua and Shen, Qiu and Yang, Ruigang and Cao, Xun},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year={2023},
publisher={IEEE}}
@inproceedings{yang2020facescape,
author = {Yang, Haotian and Zhu, Hao and Wang, Yanru and Huang, Mingkai and Shen, Qiu and Yang, Ruigang and Cao, Xun},
title = {FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020},
page = {601--610}}
The project is supported by CITE Lab of Nanjing University, Baidu Research, and Aiqiyi Inc. The student contributors: Shengyu Ji, Wei Jin, Mingkai Huang, Yanru Wang, Haotian Yang, Yidi Zhang, Yunze Xiao, Yuxin Ding, Longwei Guo, Menghua Wu, Yiyu Zhuang.