  We developed a super-resolution (SR) benchmark to analyze SR's capacity to
upscale compressed videos. Our dataset employed video codecs based on five
compression standards: H.264, H.265, H.266, AV1, and AVS3. We assessed 17
state-ofthe-art SR models using our benchmark and evaluated their ability to
preserve scene context and their susceptibility to compression artifacts. To
get an accurate perceptual ranking of SR models, we conducted a crowd-sourced
side-by-side comparison of their outputs. The benchmark is publicly available
at
https://videoprocessing.ai/benchmarks/super-resolutionfor-video-compression.html.
We also analyzed benchmark results and developed an
objective-quality-assessment metric based on the current bestperforming
objective metrics. Our metric outperforms others, according to Spearman
correlation with subjective scores for compressed video upscaling. It is
publicly available at
https://github.com/EvgeneyBogatyrev/super-resolution-metric.
