  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).
