We propose the first reference-based video superresolution (RefVSR) approach that utilizes reference videos for high-fidelity results. We focus on RefVSR in a triplecamera setting, where we aim at super-resolving a low resolution ultra-wide video utilizing wide-angle and telephoto videos. We introduce the first RefVSR network that recurrently aligns and propagates temporal reference features fused with features extracted from low-resolution frames.
2022: Junyong Lee, Myeong-Chun Lee, Sunghyun Cho, Seungyong Lee
Ranked #1 on Reference-based Video Super-Resolution on RealMCVSR Dataset
https://arxiv.org/pdf/2203.14537v1.pdf
view more