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 501–510 of 3874 papers

TitleStatusHype
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural RepresentationCode1
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in ImagingCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
Deep Burst Super-ResolutionCode1
Implicit Neural Image StitchingCode1
Implicit Transformer Network for Screen Content Image Continuous Super-ResolutionCode1
Anchor-based Plain Net for Mobile Image Super-ResolutionCode1
Improving Super-Resolution Performance using Meta-Attention LayersCode1
Adversarial Magnification to Deceive Deepfake Detection through Super ResolutionCode1
Deep Blind Super-Resolution for Satellite VideoCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified