5 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 5 cited
Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment
Haoning Wu, Liang Liao, Annan Wang +5
The proliferation of videos collected during in-the-wild natural settings has pushed the development of effective Video Quality Assessment (VQA) methodologies. Contemporary supervi…
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★ 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…