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 1961–1970 of 3874 papers

TitleStatusHype
Knowledge Rectification for Camouflaged Object Detection: Unlocking Insights from Low-Quality Data—0
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey—0
Deep priors for satellite image restoration with accurate uncertainties—0
Deep Photo Cropper and Enhancer—0
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense—0
Learning to Learn to Compress—0
L^2FMamba: Lightweight Light Field Image Super-Resolution with State Space Model—0
Deep Neural Network for Fast and Accurate Single Image Super-Resolution via Channel-Attention-based Fusion of Orientation-aware Features—0
Label-free Super-Resolution Microvessel Color Flow Imaging with Ultrasound—0
Label super-resolution networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified