PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild [PDF]
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Video quality assessment (VQA) is a challenging problem due to the numerous factors that can affect the perceptual quality of a video, \eg, content attractiveness, distortion type, motion pattern, and level. However, annotating the Mean opinion score (MOS) for videos is expensive and time-consuming, which limits the scale of VQA datasets, and poses a ...
Kun Yuan 0003 +8 more
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Deep attributes and decisions fusion for no-reference video quality analysis [PDF]
Big Data and Computing Visions, 2023 Video Quality Assessment (VQA) is a critical component of various technologies, including automated video broadcasting through displaying technologies.
Adil Baig
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No-Reference Video Quality Assessment Using Distortion Learning and Temporal Attention
IEEE Access, 2022 The rapid growth of video consumption and multimedia applications has increased the interest of the academia and industry in building tools that can evaluate perceptual video quality. Since videos might be distorted when they are captured or transmitted,
Koffi Kossi +3 more
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Review of Research on Video Quality Assessment Based on Deep Learning
Jisuanji kexue yu tansuo, 2021 Video quality assessment (VQA) is based on the subjective quality assessment results of the human eye, using models to evaluate distorted videos. It is difficult for traditional assessment methods to make subjective assessment results consistent with ...
TAN Yaya, KONG Guangqian
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Sensors, 2022 With the constantly growing popularity of video-based services and applications, no-reference video quality assessment (NR-VQA) has become a very hot research topic.
Domonkos Varga
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Video quality assessment using motion-compensated temporal filtering and manifold feature similarity. [PDF]
PLoS ONE, 2017 Well-performed Video quality assessment (VQA) method should be consistent with human visual systems for better prediction accuracy. In this paper, we propose a VQA method using motion-compensated temporal filtering (MCTF) and manifold feature similarity.
Yang Song +4 more
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MRET: Multi-resolution transformer for video quality assessment
Frontiers in Signal Processing, 2023 No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA tasks are sensitive to changes in input resolution.
Junjie Ke +4 more
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Quality Feature Learning via Multi-Channel CNN and GRU for No-Reference Video Quality Assessment
IEEE Access, 2023 Nowadays, video quality assessment (VQA) plays a vital role in video-related industries to predict human perceived video quality to maintain the quality of service.
Ngai-Wing Kwong +3 more
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Multi-Dimensional Feature Fusion Network for No-Reference Quality Assessment of In-the-Wild Videos
Sensors, 2021 Over the past few decades, video quality assessment (VQA) has become a valuable research field. The perception of in-the-wild video quality without reference is mainly challenged by hybrid distortions with dynamic variations and the movement of the ...
Jiu Jiang +4 more
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Quality assessment of user-generated video using camera motion [PDF]
, 2013 With user-generated video (UGV) becoming so popular on theWeb, the availability of a reliable quality assessment (QA) measure of UGV is necessary for improving the users’ quality of experience in videobased application.
Guo, Jinlin +9 more
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