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 1261–1270 of 3874 papers

TitleStatusHype
NNVISR: Bring Neural Network Video Interpolation and Super Resolution into Video Processing FrameworkCode1
High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage—0
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation—0
One-stage Low-resolution Text Recognition with High-resolution Knowledge TransferCode1
Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-ResolutionCode1
Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point CloudsCode1
Efficient neural supersampling on a novel gaming dataset—0
Super-Resolution Estimation of UWB Channels including the Diffuse Component -- An SBL-Inspired Approach—0
Lightweight Super-Resolution Head for Human Pose EstimationCode1
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution—0
Show:102550
← PrevPage 127 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified