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 351–360 of 3874 papers

TitleStatusHype
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and ReconstructionCode1
Deep Unfolding Network for Image Super-ResolutionCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified