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.
翻译:视频超分辨率(VSR)方法往往比图像对应方具有更多的组成部分,因为它们需要利用额外的时间维度。复杂的设计并不罕见。在本研究中,我们希望解开绳结,重新考虑VSR的一些最基本的组成部分,以四种基本功能为指导,即:推广、调整、聚合和抽样。我们通过重新使用一些以最低限度重新设计方式增加的现有组成部分,展示了简洁的管道(Basic VSR),它与许多最新算法相比,在速度和恢复质量方面实现了惊人的改进。我们进行了系统分析,以解释如何获得这种收益,并讨论了陷阱。我们进一步展示了基本VSR的可扩展性,为此提出了一个信息补充机制,并结合了宣传计划,以便利信息汇总。基本VSR及其扩展(IPOVSR)可以作为未来VSR方法的有力基线。