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Space-Time-Aware Multi-Resolution Video Enhancement

About

We consider the problem of space-time super-resolution (ST-SR): increasing spatial resolution of video frames and simultaneously interpolating frames to increase the frame rate. Modern approaches handle these axes one at a time. In contrast, our proposed model called STARnet super-resolves jointly in space and time. This allows us to leverage mutually informative relationships between time and space: higher resolution can provide more detailed information about motion, and higher frame-rate can provide better pixel alignment. The components of our model that generate latent low- and high-resolution representations during ST-SR can be used to finetune a specialized mechanism for just spatial or just temporal super-resolution. Experimental results demonstrate that STARnet improves the performances of space-time, spatial, and temporal video super-resolution by substantial margins on publicly available datasets.

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita• 2020

Related benchmarks

TaskDatasetResultRank
Video Super-ResolutionVimeo-90K Medium (test)
PSNR (dB)34.86
39
Video Super-ResolutionVimeo-90K Fast (test)
PSNR (dB)36.19
39
Video Super-ResolutionVimeo-90K Slow (test)
PSNR (dB)33.1
39
Video Super-ResolutionVimeo-90k Fast
PSNR36.19
35
Space-Time Video Super-ResolutionVid4
PSNR26.06
33
Space-Time Video Super-ResolutionVid4 (test)
PSNR26.06
31
Video Super-ResolutionVimeo-90k Slow
PSNR33.1
30
Video Super-ResolutionVimeo-90k Medium
PSNR34.86
30
Spatial-Temporal Video Super-ResolutionUCF101 x4
PSNR30.608
16
Spatial-Temporal Video Super-ResolutionVimeo90K x4
PSNR28.829
16
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