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 1121–1130 of 3874 papers

TitleStatusHype
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
Exploring Diffusion with Test-Time Training on Efficient Image Restoration—0
Exploring Multi-Scale Feature Propagation and Communication for Image Super Resolution—0
Developing a new biophysical tool to combine magneto-optical tweezers with super-resolution fluorescence microscopy—0
Deterministic Medical Image Translation via High-fidelity Brownian Bridges—0
Blind inverse problems with isolated spikes—0
Detecting disruption of HER2 membrane protein organization in cell membranes with nanoscale precision—0
Blind Image Super-Resolution with Spatial Context Hallucination—0
Analysis and Interpretation of Deep CNN Representations as Perceptual Quality Features—0
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
Show:102550
← PrevPage 113 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified