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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2501–2525 of 3874 papers

TitleStatusHype
CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors—0
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study—0
NUNet: Deep Learning for Non-Uniform Super-Resolution of Turbulent Flows—0
CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks—0
Circumventing the resolution-time tradeoff in Ultrasound Localization Microscopy by Velocity Filtering—0
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network—0
Ultra-Range Gesture Recognition using a Web-Camera in Human-Robot Interaction—0
You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors—0
ODE-Inspired Network Design for Single Image Super-Resolution—0
ChartEye: A Deep Learning Framework for Chart Information Extraction—0
Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier Samples—0
Characteristic Regularisation for Super-Resolving Face Images—0
Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution—0
Omnidirectional Video Super-Resolution using Deep Learning—0
Omniscient Video Super-Resolution—0
OmniSSR: Zero-shot Omnidirectional Image Super-Resolution using Stable Diffusion Model—0
On Adapting Randomized Nyström Preconditioners to Accelerate Variational Image Reconstruction—0
On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit—0
On-Device Text Image Super Resolution—0
Channel Splitting Network for Single MR Image Super-Resolution—0
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution—0
One Model for Two Tasks: Cooperatively Recognizing and Recovering Low-Resolution Scene Text Images by Iterative Mutual Guidance—0
ACNPU: A 4.75TOPS/W 1080P@30FPS Super Resolution Accelerator with Decoupled Asymmetric Convolution—0
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space—0
One-Shot Image Restoration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified