论文标题
重新审视视频框架插值的自适应卷积
Revisiting Adaptive Convolutions for Video Frame Interpolation
论文作者
论文摘要
视频框架的插值是随着时间的推移新颖观点的综合，是一个越来越流行的研究方向，许多新论文进一步推动了最新的现状。但是，由于每种新方法都有影响插值质量的许多变量，因此很难说出实际上对此任务重要的变量。在这项工作中，我们有些令人惊讶地表明，通过一系列微妙的低级改进，可以通过较旧，更简单的方法（即可分离的卷积）获得接近最新的结果。在此过程中，我们提出了许多直观但有效的技术来提高框架插值质量，这也有可能与适应性卷积的其他相关应用，例如爆发图像deNoing，关节图像过滤或视频预测。
Video frame interpolation, the synthesis of novel views in time, is an increasingly popular research direction with many new papers further advancing the state of the art. But as each new method comes with a host of variables that affect the interpolation quality, it can be hard to tell what is actually important for this task. In this work, we show, somewhat surprisingly, that it is possible to achieve near state-of-the-art results with an older, simpler approach, namely adaptive separable convolutions, by a subtle set of low level improvements. In doing so, we propose a number of intuitive but effective techniques to improve the frame interpolation quality, which also have the potential to other related applications of adaptive convolutions such as burst image denoising, joint image filtering, or video prediction.
