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 3151–3160 of 3874 papers

TitleStatusHype
VHS to HDTV Video Translation using Multi-task Adversarial Learning—0
Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy—0
A New Adaptive Video Super-Resolution Algorithm With Improved Robustness to Innovations—0
Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications—0
A neural lens for super-resolution biological imaging—0
Video compression with low complexity CNN-based spatial resolution adaptation—0
An Ensemble Model for Distorted Images in Real Scenarios—0
SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network—0
Soft-IntroVAE for Continuous Latent space Image Super-Resolution—0
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution—0
Show:102550
← PrevPage 316 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified