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 2951–2960 of 3874 papers

TitleStatusHype
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution FrameworkCode1
PCA-SRGAN: Incremental Orthogonal Projection Discrimination for Face Super-resolution—0
Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction—0
Pyramid Attention Networks for Image RestorationCode1
GIMP-ML: Python Plugins for using Computer Vision Models in GIMP—0
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoderCode1
Attention Based Real Image RestorationCode0
Radar Accurate Localization of UAV Swarms Based on Range Super-Resolution Method—0
RAIN: A Simple Approach for Robust and Accurate Image Classification NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified