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 2801–2810 of 3874 papers

TitleStatusHype
Real-time Surgical Environment Enhancement for Robot-Assisted Minimally Invasive Surgery Based on Super-Resolution—0
Real-Time Video Super-Resolution by Joint Local Inference and Global Parameter Estimation—0
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report—0
Benchmarking Super-Resolution Algorithms on Real Data—0
Benchmarking Burst Super-Resolution for Polarization Images: Noise Dataset and Analysis—0
Real-World Image Super Resolution via Unsupervised Bi-directional Cycle Domain Transfer Learning based Generative Adversarial Network—0
Real-World Single Image Super-Resolution Under Rainy Condition—0
Bayesian Sparse Representation for Hyperspectral Image Super Resolution—0
Real-World Super-Resolution of Face-Images from Surveillance Cameras—0
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution—0
Show:102550
← PrevPage 281 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified