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
Plasma Surrogate Modelling using Fourier Neural Operators—0
Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applications—0
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
PNEN: Pyramid Non-Local Enhanced Networks—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
PointSAGE: Mesh-independent superresolution approach to fluid flow predictions—0
Polyblur: Removing mild blur by polynomial reblurring—0
Likelihood Annealing: Fast Calibrated Uncertainty for Regression—0
Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint—0
Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report—0
Show:102550
← PrevPage 316 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified