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 701–710 of 3874 papers

TitleStatusHype
Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays—0
Learning Accurate and Enriched Features for Stereo Image Super-ResolutionCode0
Mamba-based Light Field Super-Resolution with Efficient Subspace Scanning—0
Zero-Shot Image Denoising for High-Resolution Electron MicroscopyCode1
EvTexture: Event-driven Texture Enhancement for Video Super-ResolutionCode5
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
Multi-Scale Feature Fusion using Channel Transformers for Guided Thermal Image Super Resolution—0
LFMamba: Light Field Image Super-Resolution with State Space Model—0
A Dictionary Based Approach for Removing Out-of-Focus BlurCode0
Show:102550
← PrevPage 71 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified