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 21–30 of 3874 papers

TitleStatusHype
Joint Angle and Velocity-Estimation for Target Localization in Bistatic mmWave MIMO Radar in the Presence of Clutter—0
DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion ModelsCode1
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution—0
FCA2: Frame Compression-Aware Autoencoder for Modular and Fast Compressed Video Super-ResolutionCode0
Structural Similarity-Inspired Unfolding for Lightweight Image Super-ResolutionCode1
ICME 2025 Grand Challenge on Video Super-Resolution for Video ConferencingCode1
ReGuidance: A Simple Diffusion Wrapper for Boosting Sample Quality on Hard Inverse Problems—0
Stroke-based Cyclic Amplifier: Image Super-Resolution at Arbitrary Ultra-Large Scales—0
Sampling Theory for Super-Resolution with Implicit Neural RepresentationsCode0
Grids Often Outperform Implicit Neural RepresentationsCode0
Show:102550
← PrevPage 3 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified