9 citations · 15 across the 7 of their papers we have counts for
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cs.CV2022★ 9 cited
Source-free Unsupervised Domain Adaptation for Blind Image Quality Assessment
Jianzhao Liu, Xin Li, Shukun An +1
Existing learning-based methods for blind image quality assessment (BIQA) are heavily dependent on large amounts of annotated training data, and usually suffer from a severe perfor…
cs.CV2022★ 2 cited
StyleAM: Perception-Oriented Unsupervised Domain Adaption for Non-reference Image Quality Assessment
Yiting Lu, Xin Li, Jianzhao Liu +1
Deep neural networks (DNNs) have shown great potential in non-reference image quality assessment (NR-IQA). However, the annotation of NR-IQA is labor-intensive and time-consuming,…
cs.CV2022
SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment
Jianzhao Liu, Xin Li, Yanding Peng +2
Image compression has raised widespread interest recently due to its significant importance for multimedia storage and transmission. Meanwhile, a reliable image quality assessment…