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 801–810 of 3874 papers

TitleStatusHype
Hierarchical Neural Architecture Search for Single Image Super-ResolutionCode1
Deep Blind Super-Resolution for Satellite VideoCode1
Deep Blind Video Super-resolutionCode1
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain ConnectomesCode1
Deep Burst Super-ResolutionCode1
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion ModelCode1
Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-ResolutionCode1
Deep Learning-based Face Super-Resolution: A SurveyCode1
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflowCode1
Burst Image Restoration and EnhancementCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified