CelebAHairMask-HQ is a extended dataset of CelebAMask-HQ for hair segmentation or hair matting.
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 CelebAHairMask-HQ were auto-annotated with the size of 1024 x 1024.
CelebAHairMask-HQ can be used to train and evaluate algorithms of hair segmentation, hair recognition, and GANs for hair generation and editing.
- more information about CelebAMask-HQ, see https://github.com/switchablenorms/CelebAMask-HQ
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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
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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
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CelebAMask-HQ dataset: Lee, Cheng-Han and Liu, Ziwei and Wu, Lingyun and Luo, Ping, "MaskGAN: Towards Diverse and Interactive Facial Image Manipulation", in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
- The CelebAHairMask-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 CelebAHairMask-HQ dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.
The use of this software is RESTRICTED to non-commercial research and educational purposes.