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 941–950 of 3874 papers

TitleStatusHype
Robust Reference-Based Super-Resolution With Similarity-Aware Deformable ConvolutionCode1
Joint Demosaicing and Denoising With Self GuidanceCode1
TDAN: Temporally-Deformable Alignment Network for Video Super-ResolutionCode1
Perceptual Extreme Super Resolution Network with Receptive Field BlockCode1
Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial NetworkCode1
Iterative Network for Image Super-ResolutionCode1
Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral ImageryCode1
MedSRGAN: medical images super-resolution using generative adversarial networksCode1
Super-Resolution Domain Adaptation Networks for Semantic Segmentation via Pixel and Output Level AligningCode1
Invertible Image RescalingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified