Perceptual Quality Assessment of NeRF and Neural View Synthesis Methods for Front-Facing Views

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dc.contributor.authorLiang, Hanxueen_US
dc.contributor.authorWu, Tianhaoen_US
dc.contributor.authorHanji, Paramen_US
dc.contributor.authorBanterle, Francescoen_US
dc.contributor.authorGao, Hongyunen_US
dc.contributor.authorMantiuk, Rafalen_US
dc.contributor.authorÖztireli, Cengizen_US
dc.contributor.editorBermano, Amit H.en_US
dc.contributor.editorKalogerakis, Evangelosen_US
dc.date.accessioned2024-04-30T09:08:43Z
dc.date.available2024-04-30T09:08:43Z
dc.date.issued2024
dc.description.abstractNeural view synthesis (NVS) is one of the most successful techniques for synthesizing free viewpoint videos, capable of achieving high fidelity from only a sparse set of captured images. This success has led to many variants of the techniques, each evaluated on a set of test views typically using image quality metrics such as PSNR, SSIM, or LPIPS. There has been a lack of research on how NVS methods perform with respect to perceived video quality. We present the first study on perceptual evaluation of NVS and NeRF variants. For this study, we collected two datasets of scenes captured in a controlled lab environment as well as in-the-wild. In contrast to existing datasets, these scenes come with reference video sequences, allowing us to test for temporal artifacts and subtle distortions that are easily overlooked when viewing only static images. We measured the quality of videos synthesized by several NVS methods in a well-controlled perceptual quality assessment experiment as well as with many existing state-of-the-art image/video quality metrics. We present a detailed analysis of the results and recommendations for dataset and metric selection for NVS evaluation.en_US
dc.description.number2
dc.description.sectionheadersPerceptual Rendering
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15036
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15036
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15036
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Image-based rendering; Image and video acquisition; Perception
dc.subjectComputing methodologies
dc.subjectImage
dc.subjectbased rendering
dc.subjectImage and video acquisition
dc.subjectPerception
dc.titlePerceptual Quality Assessment of NeRF and Neural View Synthesis Methods for Front-Facing Viewsen_US
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