RefVSR++: Exploiting Reference Inputs for Reference-based Video
  Super-resolution
Han Zou Masanori Suganuma Takayuki Okatani
Smartphones equipped with a multi-camera system comprising multiple cameras
with different field-of-view (FoVs) are becoming more prevalent. These camera
configurations are compatible with reference-based SR and video SR, which can
be executed simultaneously while recording video on the device. Thus, combining
these two SR methods can improve image quality. Recently, Lee et al. have
presented such a method, RefVSR. In this paper, we consider how to optimally
utilize the observations obtained, including input low-resolution (LR) video
and reference (Ref) video. RefVSR extends conventional video SR quite simply,
aggregating the LR and Ref inputs over time in a single bidirectional stream.
However, considering the content difference between LR and Ref images due to
their FoVs, we can derive the maximum information from the two image sequences
by aggregating them independently in the temporal direction. Then, we propose
an improved method, RefVSR++, which can aggregate two features in parallel in
the temporal direction, one for aggregating the fused LR and Ref inputs and the
other for Ref inputs over time. Furthermore, we equip RefVSR++ with enhanced
mechanisms to align image features over time, which is the key to the success
of video SR. We experimentally show that RefVSR++ outperforms RefVSR by over
1dB in PSNR, achieving the new state-of-the-art.