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 3611–3620 of 3874 papers

TitleStatusHype
Fast Image Super-Resolution Based on In-Place Example Regression—0
Efficient Super Resolution Using Binarized Neural Network—0
Efficient Super Resolution For Large-Scale Images Using Attentional GAN—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Efficient Terrain Stochastic Differential Efficient Terrain Stochastic Differential Equations for Multipurpose Digital Elevation Model Restoration—0
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Fast Randomized-MUSIC for mm-Wave Massive MIMO Radars—0
Advancing biological super-resolution microscopy through deep learning: a brief review—0
Fast Single Image Super-Resolution—0
Show:102550
← PrevPage 362 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified