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 551–575 of 3874 papers

TitleStatusHype
Adaptive Selection of Sampling-Reconstruction in Fourier Compressed Sensing—0
Super Resolution On Global Weather Forecasts—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localisation Microscopy with Large Tissue Displacements—0
Single-Layer Learnable Activation for Implicit Neural Representation (SL^2A-INR)—0
WaveMixSR-V2: Enhancing Super-resolution with Higher EfficiencyCode2
Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression—0
Learning Two-factor Representation for Magnetic Resonance Image Super-resolution—0
Adversarial Deep-Unfolding Network for MA-XRF Super-Resolution on Old Master Paintings Using Minimal Training Data—0
Wave-U-Mamba: An End-To-End Framework For High-Quality And Efficient Speech Super Resolution—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Low Complexity DoA-ToA Signature Estimation for Multi-Antenna Multi-Carrier Systems—0
Think Twice Before You Act: Improving Inverse Problem Solving With MCMC—0
Test-time Training for Hyperspectral Image Super-resolution—0
Learned Compression for Images and Point CloudsCode1
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks—0
Three-Dimensional, Multimodal Synchrotron Data for Machine Learning ApplicationsCode0
CWT-Net: Super-resolution of Histopathology Images Using a Cross-scale Wavelet-based Transformer—0
EDADepth: Enhanced Data Augmentation for Monocular Depth EstimationCode0
Lightweight single-image super-resolution network based on dual paths—0
Distilling Generative-Discriminative Representations for Very Low-Resolution Face Recognition—0
Single-snapshot machine learning for super-resolution of turbulence—0
Empirical Bayesian image restoration by Langevin sampling with a denoising diffusion implicit prior—0
EigenSR: Eigenimage-Bridged Pre-Trained RGB Learners for Single Hyperspectral Image Super-ResolutionCode1
Enhancing digital core image resolution using optimal upscaling algorithm: with application to paired SEM images—0
Show:102550
← PrevPage 23 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified