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 2811–2820 of 3874 papers

TitleStatusHype
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling—0
Bayesian Conditioned Diffusion Models for Inverse Problems—0
ReCamMaster: Camera-Controlled Generative Rendering from A Single Video—0
Bayesian Conditional GAN for MRI Brain Image Synthesis—0
Recognition-Guided Diffusion Model for Scene Text Image Super-Resolution—0
Reconfigurable AI Modules Aided Channel Estimation and MIMO Detection—0
Reconstruct Anything Model: a lightweight foundation model for computational imaging—0
Bayesian Based Unrolling for Reconstruction and Super-resolution of Single-Photon Lidar Systems—0
Reconstruct high-resolution multi-focal plane images from a single 2D wide field image—0
Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks—0
Show:102550
← PrevPage 282 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified