Multi-viewport based 3D convolutional neural network for 360-degree video quality assessment
Multi-viewport based 3D convolutional neural network for 360-degree video quality assessment
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Scope and Contents
Contents
360-degree videos, also known as omnidirectional or panoramic videos, provide the user an immersive experience that 2D videos cannot provide. It is crucial to access the perceived quality of the 360-degree video. 2D video quality assessment (VQA) methods are unsuitable for 360-degree videos. There are few 360-degree video quality assessment (360VQA...
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Full title
Multi-viewport based 3D convolutional neural network for 360-degree video quality assessment
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TN_cdi_proquest_journals_2659401630
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2659401630
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ISSN
1380-7501
E-ISSN
1573-7721
DOI
10.1007/s11042-022-12073-1
