# CelebAMask-HQ

**Repository Path**: o1o2oxxx/CelebAMask-HQ

## Basic Information

- **Project Name**: CelebAMask-HQ
- **Description**: A large-scale face dataset for face parsing, recognition, generation and editing.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 2
- **Created**: 2025-11-04
- **Last Updated**: 2025-11-04

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# CelebAMask-HQ

[[Paper]](https://arxiv.org/abs/1907.11922) [[Demo]](https://www.youtube.com/watch?v=T1o38DFalWs)  

![image](https://github.com/switchablenorms/CelebAMask-HQ/blob/master/images/front.jpeg)

**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](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html).

* Demo of interactive facial image manipulation

![image](https://github.com/switchablenorms/CelebAMask-HQ/blob/master/images/demo.gif)

## Sample Images

![image](https://github.com/switchablenorms/CelebAMask-HQ/blob/master/images/sample.png)

## 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

![image](https://github.com/switchablenorms/CelebAMask-HQ/blob/master/images/sample_interactive.png)

## CelebAMask-HQ Dataset Downloads
* Google Drive: [downloading link](https://drive.google.com/open?id=1badu11NqxGf6qM3PTTooQDJvQbejgbTv)
* Baidu Drive: [downloading link](https://pan.baidu.com/s/1wN1E-B1bJ7mE1mrn9loj5g)

## Related Works
* **CelebA** dataset:<br/>
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 :<br/>
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
* [SPADE-TensorFlow](https://github.com/taki0112/SPADE-Tensorflow)
* [FaceParsing-PyTorch](https://github.com/zllrunning/face-parsing.PyTorch)

## 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}
}
```