  Video super-resolution (VSR) approaches tend to have more components than the
image counterparts as they need to exploit the additional temporal dimension.
Complex designs are not uncommon. In this study, we wish to untangle the knots
and reconsider some most essential components for VSR guided by four basic
functionalities, i.e., Propagation, Alignment, Aggregation, and Upsampling. By
reusing some existing components added with minimal redesigns, we show a
succinct pipeline, BasicVSR, that achieves appealing improvements in terms of
speed and restoration quality in comparison to many state-of-the-art
algorithms. We conduct systematic analysis to explain how such gain can be
obtained and discuss the pitfalls. We further show the extensibility of
BasicVSR by presenting an information-refill mechanism and a coupled
propagation scheme to facilitate information aggregation. The BasicVSR and its
extension, IconVSR, can serve as strong baselines for future VSR approaches.
