Compressed Video Quality Assessment for Super-Resolution: a Benchmark and a Quality Metric

CoRR(2023)

引用 0|浏览5
暂无评分
摘要
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.
更多
查看译文
关键词
compressed video quality assessment,benchmark,super-resolution
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要