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 161–170 of 3874 papers

TitleStatusHype
DSSR-Net for Super-Resolution Radar Range Profiles—0
GAMBAS: Generalised-Hilbert Mamba for Super-resolution of Paediatric Ultra-Low-Field MRICode0
MIMRS: A Survey on Masked Image Modeling in Remote Sensing—0
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution—0
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion RefinementCode2
Representing Flow Fields with Divergence-Free Kernels for Reconstruction—0
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB ImageCode1
GSR4B: Biomass Map Super-Resolution with Sentinel-1/2 GuidanceCode1
NCAP: Scene Text Image Super-Resolution with Non-CAtegorical PriorCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified