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 1976–2000 of 3874 papers

TitleStatusHype
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on RegressionCode0
SR-GAN for SR-gamma: super resolution of photon calorimeter images at collider experiments—0
S2R: Exploring a Double-Win Transformer-Based Framework for Ideal and Blind Super-ResolutionCode0
Dynamic Attention-Guided Diffusion for Image Super-Resolution—0
CMISR: Circular Medical Image Super-Resolution—0
On Versatile Video Coding at UHD with Machine-Learning-Based Super-Resolution—0
Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment TechnologyCode0
A Self-Supervised Deep Denoiser for Hyperspectral and Multispectral Image FusionCode0
Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems—0
HSD-PAM: High Speed Super Resolution Deep Penetration Photoacoustic Microscopy Imaging Boosted by Dual Branch Fusion Network—0
Harnessing Artificial Intelligence To Reduce Phototoxicity in Live Imaging—0
PSRFlow: Probabilistic Super Resolution with Flow-Based Models for Scientific Data—0
When Super-Resolution Meets Camouflaged Object Detection: A Comparison Study—0
High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage—0
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation—0
Super-Resolution Estimation of UWB Channels including the Diffuse Component -- An SBL-Inspired Approach—0
Efficient neural supersampling on a novel gaming dataset—0
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution—0
RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid SubjectsCode0
Recovering high-quality FODs from a reduced number of diffusion-weighted images using a model-driven deep learning architectureCode0
A full-resolution training framework for Sentinel-2 image fusion—0
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting—0
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified