7 citations · 16 across the 7 of their papers we have counts for
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cs.MM2021★ 2 cited
Learning from Synthetic Data for Opinion-free Blind Image Quality Assessment in the Wild
Zhihua Wang, Zhi-Ri Tang, Jianguo Zhang +1
Nowadays, most existing blind image quality assessment (BIQA) models 1) are developed for synthetically-distorted images and often generalize poorly to authentic ones; 2) heavily r…
cs.CV2021★ 7 cited
Semi-Supervised Deep Ensembles for Blind Image Quality Assessment
Zhihua Wang, Dingquan Li, Kede Ma
Ensemble methods are generally regarded to be better than a single model if the base learners are deemed to be "accurate" and "diverse." Here we investigate a semi-supervised ensem…
cs.CV2021★ 2 cited
Troubleshooting Blind Image Quality Models in the Wild
Zhihua Wang, Haotao Wang, Tianlong Chen +2
Recently, the group maximum differentiation competition (gMAD) has been used to improve blind image quality assessment (BIQA) models, with the help of full-reference metrics. When…