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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1811–1820 of 3874 papers

TitleStatusHype
Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution—0
IMDeception: Grouped Information Distilling Super-Resolution Network—0
Deep multi-frame face super-resolution—0
Deep MR Image Super-Resolution Using Structural Priors—0
Image Restoration using Autoencoding Priors—0
Progressive Image Super-Resolution via Neural Differential Equation—0
Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors—0
BERT-PIN: A BERT-based Framework for Recovering Missing Data Segments in Time-series Load Profiles—0
Image Restoration by Deep Projected GSURE—0
Image Resolution Enhancement by Using Interpolation Followed by Iterative Back Projection—0
Show:102550
← PrevPage 182 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified