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 1101–1110 of 3874 papers

TitleStatusHype
A Spectral Diffusion Prior for Hyperspectral Image Super-ResolutionCode1
RBPGAN: Recurrent Back-Projection GAN for Video Super Resolution—0
Texture and Noise Dual Adaptation for Infrared Image Super-ResolutionCode0
The Perception-Robustness Tradeoff in Deterministic Image Restoration—0
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR ImagesCode0
Learning based Deep Disentangling Light Field Reconstruction and Disparity Estimation Application—0
A Lightweight Recurrent Aggregation Network for Satellite Video Super-ResolutionCode1
Improved Pothole Detection Using YOLOv7 and ESRGANCode0
Plasma Surrogate Modelling using Fourier Neural Operators—0
OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified