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 1931–1940 of 3874 papers

TitleStatusHype
Neural Operators for Accelerating Scientific Simulations and Design—0
Uncertainty Quantification via Neural Posterior Principal Components—0
Style Transfer and Self-Supervised Learning Powered Myocardium Infarction Super-Resolution SegmentationCode0
Guided Frequency Loss for Image Restoration—0
An Ensemble Model for Distorted Images in Real Scenarios—0
DONNAv2 -- Lightweight Neural Architecture Search for Vision tasks—0
Data Upcycling Knowledge Distillation for Image Super-ResolutionCode0
A Lightweight Recurrent Grouping Attention Network for Video Super-ResolutionCode0
Adaptation of the super resolution SOTA for Art Restoration in camera capture imagesCode0
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data—0
Show:102550
← PrevPage 194 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified