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 831–840 of 3874 papers

TitleStatusHype
Real-World Single Image Super-Resolution: A Brief ReviewCode1
Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution EnhancementCode1
Super-resolution-based Change Detection Network with Stacked Attention Module for Images with Different ResolutionsCode1
SRDTI: Deep learning-based super-resolution for diffusion tensor MRICode1
Intermediate Layer Optimization for Inverse Problems using Deep Generative ModelsCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity AttackCode1
Exploiting Raw Images for Real-Scene Super-ResolutionCode1
Learning Non-linear Wavelet Transformation via Normalizing FlowCode1
Deep Burst Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified