Generic face image quality assessment databaseDespite the fact that the study of face images is an important sub-field in computer vision research, the lack of face IQA data and models limits the precision of current IQA metrics on face image processing tasks such as face super-resolution, face enhancement, and face editing. To narrow the gap, we created the largest IQA database of human faces in-the-wild called the Generic face image quality assessment 20k database (GFIQA-20k), in which 20,000 face images were rated and ensured the diversity of the individuals depicted in highly varied circumstances. |
Cite usGFIQA-20k is freely available to the research community. If you use our database in your research, you can cite it as follows:
@article{gfiqa20k, title={Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model}, author={Su, Shaolin and Lin, Hanhe and Hosu, Vlad and Wiedemann, Oliver and Sun, Jinqiu and Zhu, Yu and Liu, Hantao and Zhang, Yanning and Saupe, Dietmar}, journal={arXiv preprint arXiv:2207.04904}, year={2022}} |
Download
~7.2 GB
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The GFIQA-20k database contains:
"images" folder: contains all images. "jpeg" folder: contains all images compressed by JPEG. "mos_var_rating.csv" file: contains subjective ratings. |