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 1501–1550 of 3874 papers

TitleStatusHype
Super Resolution On Global Weather Forecasts—0
Single-Layer Learnable Activation for Implicit Neural Representation (SL^2A-INR)—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression—0
Learning Two-factor Representation for Magnetic Resonance Image Super-resolution—0
Wave-U-Mamba: An End-To-End Framework For High-Quality And Efficient Speech Super Resolution—0
Adversarial Deep-Unfolding Network for MA-XRF Super-Resolution on Old Master Paintings Using Minimal Training Data—0
Think Twice Before You Act: Improving Inverse Problem Solving With MCMC—0
Low Complexity DoA-ToA Signature Estimation for Multi-Antenna Multi-Carrier Systems—0
Test-time Training for Hyperspectral Image Super-resolution—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks—0
CWT-Net: Super-resolution of Histopathology Images Using a Cross-scale Wavelet-based Transformer—0
Three-Dimensional, Multimodal Synchrotron Data for Machine Learning ApplicationsCode0
Lightweight single-image super-resolution network based on dual paths—0
EDADepth: Enhanced Data Augmentation for Monocular Depth EstimationCode0
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
Use of triplet loss for facial restoration in low-resolution images—0
Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization ProblemCode0
aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio—0
Enhancing digital core image resolution using optimal upscaling algorithm: with application to paired SEM images—0
Solving Video Inverse Problems Using Image Diffusion Models—0
SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution—0
EarthGen: Generating the World from Top-Down ViewsCode0
Attention-Guided Multi-scale Interaction Network for Face Super-Resolution—0
DMRA: An Adaptive Line Spectrum Estimation Method through Dynamical Multi-Resolution of Atoms—0
HiTSR: A Hierarchical Transformer for Reference-based Super-ResolutionCode0
Beyond MR Image Harmonization: Resolution Matters Too—0
GameIR: A Large-Scale Synthesized Ground-Truth Dataset for Image Restoration over Gaming Content—0
Super-Resolution works for coastal simulations—0
Enhanced Control for Diffusion Bridge in Image RestorationCode0
ChartEye: A Deep Learning Framework for Chart Information Extraction—0
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment—0
Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-ResolutionCode0
A Preliminary Exploration Towards General Image Restoration—0
Particle-Filtering-based Latent Diffusion for Inverse Problems—0
FreqINR: Frequency Consistency for Implicit Neural Representation with Adaptive DCT Frequency Loss—0
SIMPLE: Simultaneous Multi-Plane Self-Supervised Learning for Isotropic MRI Restoration from Anisotropic Data—0
ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral ImagesCode0
A Unified Plug-and-Play Algorithm with Projected Landweber Operator for Split Convex Feasibility Problems—0
3D Photon Counting CT Image Super-Resolution Using Conditional Diffusion Model—0
Joint Reconstruction and Spatial Super-Resolution of Hyper-Spectral CTIS Images via Multi-Scale RefinementCode0
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling—0
Harnessing Multi-resolution and Multi-scale Attention for Underwater Image RestorationCode0
Webcam-based Pupil Diameter Prediction Benefits from UpscalingCode0
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving TransformerCode0
Angle of Arrival Estimation with Transformer: A Sparse and Gridless Method with Zero-Shot Capability—0
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified