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 461–470 of 3874 papers

TitleStatusHype
Decoupling Fine Detail and Global Geometry for Compressed Depth Map Super-ResolutionCode0
MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D—0
Super-Resolution without High-Resolution Labels for Black Hole SimulationsCode0
Constrained Diffusion Implicit Models—0
Blind Time-of-Flight Imaging: Sparse Deconvolution on the Continuum with Unknown Kernels—0
DiffPAD: Denoising Diffusion-based Adversarial Patch DecontaminationCode0
Enhancing Image Resolution: A Simulation Study and Sensitivity Analysis of System Parameters for Resourcesat-3S/3SA—0
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture ModelsCode2
Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing ImagesCode0
Temporal and Spatial Super Resolution with Latent Diffusion Model in Medical MRI images—0
Show:102550
← PrevPage 47 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified