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 171–180 of 3874 papers

TitleStatusHype
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Investigating Tradeoffs in Real-World Video Super-ResolutionCode2
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation ModelCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
Lossless Image Compression through Super-ResolutionCode2
A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact RemovalCode2
CoSeR: Bridging Image and Language for Cognitive Super-ResolutionCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified