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RIRNet: Recurrent-In-Recurrent Network for Video Quality Assessment
ACM Multimedia, 2020Video quality assessment (VQA), which is capable of automatically predicting the perceptual quality of source videos especially when reference information is not available, has become a major concern for video service providers due to the growing demand ...
Pengfei Chen +4 more
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Video quality monitoring of streamed videos
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009This paper describes a video quality analysis system for inservice monitoring of streamed videos, particularly over mobile/wireless networks. The algorithm adopts the no-reference method, and enables real-time measurement of video quality at any point in the content production and delivery chain using any given video. The technologies developed include
Ee Ping Ong +6 more
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COVER: A Comprehensive Video Quality Evaluator
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)Video quality assessment, especially for a massive scale of user-generated content, is an essential yet challenging computer vision and video analysis problem.
Chenlong He +5 more
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No-Reference Video Quality Assessment Using Natural Spatiotemporal Scene Statistics
IEEE Transactions on Image Processing, 2020Robust spatiotemporal representations of natural videos have several applications including quality assessment, action recognition, object tracking etc.
Sathya Veera Reddy Dendi +1 more
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Video classification for video quality prediction
Journal of Zhejiang University-SCIENCE A, 2006In this paper we propose a novel method for video quality prediction using video classification. In essence, our approach can serve two goals: (1) To measure the video quality of compressed video sequences without referencing to the original uncompressed videos, i.e., to realize No-Reference (NR) video quality evaluation; (2) To predict quality scores ...
Yu-xin Liu, Ragip Kurceren, Udit Budhia
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Two-Level Approach for No-Reference Consumer Video Quality Assessment
IEEE Transactions on Image Processing, 2019Smartphones and other consumer devices capable of capturing video content and sharing it on social media in nearly real time are widely available at a reasonable cost.
J. Korhonen
semanticscholar +1 more source
2014
Abstract Measuring video quality is one of the most critical and yet challenging tasks for video processing applications. It enables the assessment of video quality off-line, providing a basis for validation and comparison of codec performance, and it also facilitates rate-quality optimization within the coding loop for on-line compression ...
Fan Zhang, David R. Bull
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Abstract Measuring video quality is one of the most critical and yet challenging tasks for video processing applications. It enables the assessment of video quality off-line, providing a basis for validation and comparison of codec performance, and it also facilitates rate-quality optimization within the coding loop for on-line compression ...
Fan Zhang, David R. Bull
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MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
International Conference on Machine LearningIn recent years, generative artificial intelligence has achieved significant advancements in the field of image generation, spawning a variety of applications.
Yuang Zhang +6 more
semanticscholar +1 more source
The difference between perceived video quality and objective video quality
Journal of Visualization, 2009We select 93 video sequences encoded/decoded by Microsoft MPEG-4 software to classify them into six different content characteristics by the cluster analysis and the discriminant analysis in this study. We compare the peak signal noise ratio (PSNR) of objective video quality evaluation with the mean opinion score of subjective quality evaluation to ...
Huey-Min Sun, Yan-Kai Huang
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Subjective video quality prediction based on objective video quality metrics
2018 4th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), 2018This A method is proposed for the generation of a set of video sequence with a predictive subjective video quality (Mean Opinion Score) based on a limited number of sequences and the associated objective video quality measure (Peak Signal-to-Noise Ratio). The MOS is predicted using a sigmoid function model that is optimized based on a limited number of
M. Alizadeh, M. Sharifkhani
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