switchablenorms/CelebAMask-HQ
switchablenorms/CelebAMask-HQ has 2,330 GitHub stars and 355 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-06 22:37 UTC. Last push 2024-06-20.
A large-scale face dataset for face parsing, recognition, generation and editing.
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README.md
OriginalCelebAMask-HQ

CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA dataset by following CelebA-HQ. Each image has segmentation mask of facial attributes corresponding to CelebA.
The masks of CelebAMask-HQ were manually-annotated with the size of 512 x 512 and 19 classes including all facial components and accessories such as skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, and cloth.
CelebAMask-HQ can be used to train and evaluate algorithms of face parsing, face recognition, and GANs for face generation and editing.
If you need the identity labels and the attribute labels of the images, please send request to the CelebA team.
Demo of interactive facial image manipulation

Sample Images

Face Manipulation Model with CelebAMask-HQ
CelebAMask-HQ can be used on several research fields including: facial image manipulation, face parsing, face recognition, and face hallucination. We showcase an application on interactive facial image manipulation as bellow:
- Samples of interactive facial image manipulation

CelebAMask-HQ Dataset Downloads
- Google Drive: downloading link
- Baidu Drive: downloading link
Related Works
- CelebA dataset:
Ziwei Liu, Ping Luo, Xiaogang Wang and Xiaoou Tang, "Deep Learning Face Attributes in the Wild", in IEEE International Conference on Computer Vision (ICCV), 2015 - CelebA-HQ was collected from CelebA and further post-processed by the following paper :
Karras et. al, "Progressive Growing of GANs for Improved Quality, Stability, and Variation", in Internation Conference on Reoresentation Learning (ICLR), 2018
Dataset Agreement
- The CelebAMask-HQ dataset is available for non-commercial research purposes only.
- You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
- You agree not to further copy, publish or distribute any portion of the CelebAMask-HQ dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.
Related Projects using CelebAMask-HQ
License and Citation
The use of this software is RESTRICTED to non-commercial research and educational purposes.
@inproceedings{CelebAMask-HQ,
title={MaskGAN: Towards Diverse and Interactive Facial Image Manipulation},
author={Lee, Cheng-Han and Liu, Ziwei and Wu, Lingyun and Luo, Ping},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}
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