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 3531–3540 of 3874 papers

TitleStatusHype
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-ResolutionCode0
LAR-SR: A Local Autoregressive Model for Image Super-ResolutionCode0
Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-ResolutionCode0
Practical Manipulation Model for Robust Deepfake DetectionCode0
Laplacian Pyramid-like AutoencoderCode0
Unsupervised and Unregistered Hyperspectral Image Super-Resolution with Mutual Dirichlet-NetCode0
EarthGen: Generating the World from Top-Down ViewsCode0
E2FIF: Push the limit of Binarized Deep Imagery Super-resolution using End-to-end Full-precision Information FlowCode0
Dynamic Structured Illumination Microscopy with a Neural Space-time ModelCode0
LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled VariablesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified