5 citations · 9 across the 3 of their papers we have counts for
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cs.CV2023★ 2 cited
Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterion
Haoning Wu, Liang Liao, Jingwen Hou +6
Recent learning-based video quality assessment (VQA) algorithms are expensive to implement due to the cost of data collection of human quality opinions, and are less robust across…
cs.CV2022★ 2 cited
Exploring the Effectiveness of Video Perceptual Representation in Blind Video Quality Assessment
Liang Liao, Kangmin Xu, Haoning Wu +4
With the rapid growth of in-the-wild videos taken by non-specialists, blind video quality assessment (VQA) has become a challenging and demanding problem. Although lots of efforts…
cs.CV2022★ 5 cited
FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling
Haoning Wu, Chaofeng Chen, Jingwen Hou +5
Current deep video quality assessment (VQA) methods are usually with high computational costs when evaluating high-resolution videos. This cost hinders them from learning better vi…