61 citations · 114 across the 10 of their papers we have counts for
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cs.CV2020★ 1 cited
Cuid: A new study of perceived image quality and its subjective assessment
Lucie Lévêque, Ji Yang, Xiaohan Yang +5
Research on image quality assessment (IQA) remains limited mainly due to our incomplete knowledge about human visual perception. Existing IQA algorithms have been designed or train…
cs.CV2020
Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network
Qian Ning, Weisheng Dong, Guangming Shi +2
Deep neural networks (DNNs) based methods have achieved great success in single image super-resolution (SISR). However, existing state-of-the-art SISR techniques are designed like…
eess.IV2020★ 21 cited
MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessment
Hancheng Zhu, Leida Li, Jinjian Wu +2
Recently, increasing interest has been drawn in exploiting deep convolutional neural networks (DCNNs) for no-reference image quality assessment (NR-IQA). Despite of the notable suc…