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 1761–1770 of 3874 papers

TitleStatusHype
Efficient Hair Style Transfer with Generative Adversarial Networks—0
Boomerang: Local sampling on image manifolds using diffusion models—0
Single Image Super-Resolution Using Lightweight Networks Based on Swin Transformer—0
Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report—0
Super-Resolution and Image Re-projection for Iris Recognition—0
Real Image Super-Resolution using GAN through modeling of LR and HR process—0
Provably Convergent Plug & Play Linearized ADMM, applied to Deblurring Spatially Varying KernelsCode0
Video super-resolution for single-photon LIDAR—0
Very Low-Resolution Iris Recognition Via Eigen-Patch Super-Resolution and Matcher Fusion—0
Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks—0
Show:102550
← PrevPage 177 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified