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author:

Niu, Yuzhen (Niu, Yuzhen.) [1] | Zheng, Yuming (Zheng, Yuming.) [2] | Wang, Zhenlong (Wang, Zhenlong.) [3] | Zhong, Mengzhen (Zhong, Mengzhen.) [4] | Zhao, Tiesong (Zhao, Tiesong.) [5]

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Abstract:

Blind quality assessment for user-generated content (UGC) or consumer videos is challenging in computer vision. Two open issues are yet to be addressed: how to effectively extract high-dimensional spatial-temporal features of consumer videos and how to appropriately model the relationship between these features and user perceptions within a unified blind video quality assessment (BVQA). To tackle these issues, we propose a novel BVQA model with spatial-temporal perception and fusion. Firstly, we develop two perception modules to extract the perceptual-distortion-related features separately from the spatial and temporal domains. In particular, the temporal-domain features are obtained with a combination of 3D ConvNet and residual frames for their high efficiencies in capturing the motion-specific temporal features. Secondly, we propose a feature fusion module that adaptively combines spatial-temporal features. Finally, we map the fused features onto perceptual quality. Experimental results demonstrate that our model outperforms other advanced methods in conducting subjective video quality prediction. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

Keyword:

Image quality

Community:

  • [ 1 ] [Niu, Yuzhen]College of Computer and Data Science, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Niu, Yuzhen]College of Physics and Information Engineering, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Zheng, Yuming]College of Computer and Data Science, Fuzhou University, Fuzhou; 350116, China
  • [ 4 ] [Wang, Zhenlong]College of Computer and Data Science, Fuzhou University, Fuzhou; 350116, China
  • [ 5 ] [Zhong, Mengzhen]College of Computer and Data Science, Fuzhou University, Fuzhou; 350116, China
  • [ 6 ] [Zhao, Tiesong]College of Physics and Information Engineering, Fuzhou University, Fuzhou; 350108, China

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Source :

Multimedia Tools and Applications

ISSN: 1380-7501

Year: 2024

Issue: 7

Volume: 83

Page: 18969-18986

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JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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