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 1611–1620 of 3874 papers

TitleStatusHype
V2X Sidelink Positioning in FR1: From Ray-Tracing and Channel Estimation to Bayesian Tracking—0
Burst Image Super-Resolution with Base Frame Selection—0
A Near-Field Super-Resolution Network for Accelerating Antenna Characterization—0
Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution—0
Improving Generative Adversarial Networks for Video Super-Resolution—0
Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays—0
Mamba-based Light Field Super-Resolution with Efficient Subspace Scanning—0
Learning Accurate and Enriched Features for Stereo Image Super-ResolutionCode0
IG-CFAT: An Improved GAN-Based Framework for Effectively Exploiting Transformers in Real-World Image Super-ResolutionCode0
Enhance the Image: Super Resolution using Artificial Intelligence in MRI—0
Show:102550
← PrevPage 162 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified