Info hash | b5738811260a33d02bfb781f7251b15bee7bb987 |
Last mirror activity | 21:52:00 ago |
Size | 3.15GB (3,153,930,546 bytes) |
Added | 2022-08-13 04:17:36 |
Views | 95 |
Hits | 446 |
ID | 4833 |
Type | single |
Downloaded | 253 time(s) |
Uploaded by | joecohen |
Filename | CelebAMask-HQ.zip |
Mirrors | 3 complete, 0 downloading = 3 mirror(s) total [Log in to see full list] |
CelebAMask-HQ.zip | 3.15GB |
Type: Dataset
Tags: face, celeba, celeb
Bibtex:
Tags: face, celeba, celeb
Bibtex:
@article{, title= {CelebAMask-HQ}, keywords= {Face, celeb, celeba}, author= {}, abstract= {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. ## Sample Images https://raw.githubusercontent.com/switchablenorms/CelebAMask-HQ/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 ## 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} } ``` }, terms= {}, license= {}, superseded= {}, url= {https://github.com/switchablenorms/CelebAMask-HQ} }