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 3731–3740 of 3874 papers

TitleStatusHype
Teaching deep neural networks to localize single molecules for super-resolution microscopyCode0
Trustworthy Image Super-Resolution via Generative PseudoinverseCode0
HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion PriorCode0
tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid FlowCode0
Residual Non-local Attention Networks for Image RestorationCode0
HiTSR: A Hierarchical Transformer for Reference-based Super-ResolutionCode0
StofNet: Super-resolution Time of Flight NetworkCode0
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and ResultsCode0
Store and Fetch Immediately: Everything Is All You Need for Space-Time Video Super-resolutionCode0
Deeply-Recursive Convolutional Network for Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified