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}}
|
Sampled face images with their corresponding MOS (white digits)
