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 991–1000 of 3874 papers

TitleStatusHype
Diffusion-based Blind Text Image Super-ResolutionCode1
Blockwise Parallel Decoding for Deep Autoregressive ModelsCode1
Blueprint Separable Residual Network for Efficient Image Super-ResolutionCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
Enhancement of Anime Imaging Enlargement using Modified Super-Resolution CNNCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
EgoVSR: Towards High-Quality Egocentric Video Super-ResolutionCode1
Transformer for Single Image Super-ResolutionCode1
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and ReconstructionCode1
Efficient Video Compression via Content-Adaptive Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified