Title: Detail-revealing Deep Video Super-resolution,
Abstract: Previous CNN-based video super-resolution approaches need to align multiple
frames to the reference. In this paper, we show that proper frame alignment and
motion compensation is crucial for achieving high quality results. We
accordingly propose a `sub-pixel motion compensation' (SPMC) layer in a CNN
framework. Analysis and experiments show the suitability of this layer in video
SR. The final end-to-end, scalable CNN framework effectively incorporates the
SPMC layer and fuses multiple frames to reveal image details. Our
implementation can generate visually and quantitatively high-quality results,
superior to current state-of-the-arts, without the need of parameter tuning.