Real-Time Video Deblurring via Lightweight Motion Compensation

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dc.contributor.authorSon, Hyeongseoken_US
dc.contributor.authorLee, Junyongen_US
dc.contributor.authorCho, Sunghyunen_US
dc.contributor.authorLee, Seungyongen_US
dc.contributor.editorUmetani, Nobuyukien_US
dc.contributor.editorWojtan, Chrisen_US
dc.contributor.editorVouga, Etienneen_US
dc.date.accessioned2022-10-04T06:39:41Z
dc.date.available2022-10-04T06:39:41Z
dc.date.issued2022
dc.description.abstractWhile motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead. This paper proposes a real-time video deblurring framework consisting of a lightweight multi-task unit that supports both video deblurring and motion compensation in an efficient way. The multi-task unit is specifically designed to handle large portions of the two tasks using a single shared network and consists of a multi-task detail network and simple networks for deblurring and motion compensation. The multi-task unit minimizes the cost of incorporating motion compensation into video deblurring and enables real-time deblurring. Moreover, by stacking multiple multi-task units, our framework provides flexible control between the cost and deblurring quality. We experimentally validate the state-of-theart deblurring quality of our approach, which runs at a much faster speed compared to previous methods and show practical real-time performance (30.99dB@30fps measured on the DVD dataset).en_US
dc.description.number7
dc.description.sectionheadersVideo
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14667
dc.identifier.issn1467-8659
dc.identifier.pages177-188
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14667
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14667
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies --> Computational photography
dc.subjectComputing methodologies
dc.subjectComputational photography
dc.titleReal-Time Video Deblurring via Lightweight Motion Compensationen_US
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