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

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Showing 451–475 of 3874 papers

TitleStatusHype
AEROMamba: An efficient architecture for audio super-resolution using generative adversarial networks and state space modelsCode2
General Geospatial Inference with a Population Dynamics Foundation ModelCode3
SuperResolution Radar Gesture Recognitio—0
Local Implicit Wavelet Transformer for Arbitrary-Scale Super-ResolutionCode1
Quasi-Newton OMP Approach for Super-Resolution Channel Estimation and Extrapolation—0
A Modular Conditional Diffusion Framework for Image Reconstruction—0
Electro-diffusive modeling and the role of spine geometry on action potential propagation in neurons—0
WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning—0
ESC-MISR: Enhancing Spatial Correlations for Multi-Image Super-Resolution in Remote Sensing—0
SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision AgricultureCode0
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
Fingerprints of Super Resolution Networks—0
Volumetric Conditioning Module to Control Pretrained Diffusion Models for 3D Medical ImagesCode1
Learning Optimal Combination Patterns for Lightweight Stereo Image Super-Resolution—0
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
A Generative Diffusion Model to Solve Inverse Problems for Robust in-NICU Neonatal MRI—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified