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CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms
IEEE Transactions on Image Processing, 2016In this paper, we present a new video database: CVD2014-Camera Video Database. In contrast to previous video databases, this database uses real cameras rather than introducing distortions via post-processing, which results in a complex distortion space in regard to the video acquisition process.
Virtanen, Toni +6 more
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A Lightweight No-reference Video Quality Assessment Method
2023 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2023Huiying Shi +3 more
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CNN-MR for No Reference Video Quality Assessment
2017 4th International Conference on Information Science and Control Engineering (ICISCE), 2017In this paper, we propose a no-reference video quality assessment (VQA) method based on Convolutional Neural Network (CNN) and Multi-Regression (CNN-MR). It is universal for non-specific types of distortion. First, we innovatively introduce the 2D convolutional neural network into VQA model to learn the spatial quality features at frame level.
Chunfeng Wang, Li Su, Qingming Huang
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A novel no-reference video quality assessment algorithm
2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), 2018The no-reference video quality evaluation method has become a hotspot and difficulty for video quality evaluation research due to its convenience and lack of reference information. This paper proposed a spatio-temporal domain combined no-reference video quality assessment method.
Lin Yang, Yingyun Yang, Yong Ma
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Reconstruction-based no-reference video quality assessment
2016 IEEE Region 10 Conference (TENCON), 2016Video quality assessment is one of the key techniques in video communication and editing. With constraints of transmission system, storage space etc., original information of videos may not be available. No-reference video quality assessment (NRVQA) methods are in demand.
Zhenyu Wu, Hong Hu
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Analysis and Modelling of No-Reference Video Quality Assessment
2009 International Conference on Computer and Automation Engineering, 2009Video processing system may introduce some amounts of distortions in the video signal. It is crucial to measure the video quality blindly for most image processing applications which could not obtain the original image. Different Video Quality Assessment (VQA) methods are analysis in this paper.
null Yuan Tian, null Ming Zhu
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No reference video-quality-assessment model for video streaming services
2010 18th International Packet Video Workshop, 2010We propose a no reference video-quality-assessment model for estimating the quality of experience (QoE) of video streaming services using quality features derived from decoded video signals. The proposed model is useful as a QoE monitoring tool for video streaming services.
Taichi Kawano +3 more
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No-reference omnidirectional video quality assessment based on generative adversarial networks
Multimedia Tools and Applications, 2021Yao Luo, Luo Yao
exaly
Full-Reference and No-Reference Quality Assessment for Video Frame Interpolation
IEEE Transactions on Circuits and Systems for Video TechnologyJinliang Han +5 more
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Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing
IEEE Transactions on Circuits and Systems for Video Technology, 2013Rajiv Soundararajan, Alan Bovik
exaly