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 1011–1020 of 3874 papers

TitleStatusHype
Single particle algorithms to reveal cellular nanodomain organization—0
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned GuidanceCode1
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction—0
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—0
A Survey on Super Resolution for video Enhancement Using GAN—0
Perception-Distortion Balanced Super-Resolution: A Multi-Objective Optimization PerspectiveCode1
BSRAW: Improving Blind RAW Image Super-Resolution—0
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion ModelsCode2
A Comprehensive End-to-End Computer Vision Framework for Restoration and Recognition of Low-Quality Engineering DrawingsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified