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 2711–2720 of 3874 papers

TitleStatusHype
Learned super resolution ultrasound for improved breast lesion characterization—0
Image restoration quality assessment based on regional differential information entropy—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
Blind Image Super-Resolution: A Survey and Beyond—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
From General to Specific: Online Updating for Blind Super-Resolution—0
Impact of deep learning-based image super-resolution on binary signal detection—0
Show:102550
← PrevPage 272 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified