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).

翻译：虽然运动补偿大大提高了视频破碎质量,单独执行运动补偿和视频破碎要求巨大的计算间接费用,但本文提议了一个实时视频破碎框架,由轻量多任务单位组成,以高效的方式支持视频破碎和运动补偿。多任务单位专门设计用来使用单一共享网络处理大部分两项任务,由多任务细节网络和简单的拆解和运动补偿网络组成。多任务单位尽量减少了将运动补偿纳入视频破碎和实时拆解的成本。此外,通过堆叠多个任务单位,我们的框架在成本和拆解质量之间提供了灵活的控制。我们实验性地验证了我们方法的先进拆碎质量,与以往方法相比速度要快得多,并显示实际实时性能(DVD数据集测量的30.99dB@30fps )。