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 3171–3180 of 3874 papers

TitleStatusHype
Precipitation Downscaling with Spatiotemporal Video Diffusion—0
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties—0
Process of image super-resolution—0
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Progressive Generative Adversarial Networks for Medical Image Super resolution—0
Progressively Unfreezing Perceptual GAN—0
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution—0
Prompt-tuning latent diffusion models for inverse problems—0
Propagation Modeling for Physically Large Arrays: Measurements and Multipath Component Visibility—0
Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified