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.
Due to insufficient computing resources, the V1.0 version of this dataset is not good enough.I will update the new one later.
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
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 use of this software is RESTRICTED to non-commercial research and educational purposes.