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arXiv · 2205.12634

Real-Time Video Deblurring via Lightweight Motion Compensation

Hyeongseok Son·Junyong Lee·Sunghyun Cho·Seungyong Lee
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Abstract

While 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-the-art 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 in the DVD dataset).

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Hyeongseok Son, Junyong Lee, Sunghyun Cho, Seungyong Lee. 2022-05-25. Real-Time Video Deblurring via Lightweight Motion Compensation. https://doi.org/10.1111/cgf.14667

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