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 721–730 of 3874 papers

TitleStatusHype
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural RepresentationCode1
Improving Super-Resolution Performance using Meta-Attention LayersCode1
Fusion of complementary 2D and 3D mesostructural datasets using generative adversarial networksCode1
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
EFENet: Reference-based Video Super-Resolution with Enhanced Flow EstimationCode1
Gradient Step Denoiser for convergent Plug-and-PlayCode1
Burst Image Restoration and EnhancementCode1
Enhancement of Anime Imaging Enlargement using Modified Super-Resolution CNNCode1
A Systematic Survey of Deep Learning-based Single-Image Super-ResolutionCode1
Structure-Preserving Image Super-ResolutionCode1
Show:102550
← PrevPage 73 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified