SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 2901–2910 of 3874 papers

TitleStatusHype
Turning Frequency to Resolution: Video Super-Resolution via Event Cameras—0
TV-based Deep 3D Self Super-Resolution for fMRI—0
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution—0
Two-dimensional gridless super-resolution method for ISAR imaging—0
Two-phase Hair Image Synthesis by Self-Enhancing Generative Model—0
Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution—0
UB-FineNet: Urban Building Fine-grained Classification Network for Open-access Satellite Images—0
UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt—0
UDC: Unified DNAS for Compressible TinyML Models—0
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified