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 801–810 of 3874 papers

TitleStatusHype
Generative Diffusion-based Downscaling for ClimateCode2
Federated Learning for Blind Image Super-Resolution—0
One-Shot Image Restoration—0
Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion ModelCode1
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time seriesCode1
Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge SurveyCode3
Deep learning-based blind image super-resolution with iterative kernel reconstruction and noise estimationCode0
Latent Modulated Function for Computational Optimal Continuous Image RepresentationCode2
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey—0
A Survey on Visual MambaCode4
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified