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 2601–2625 of 3874 papers

TitleStatusHype
High-Resolution WiFi Imaging with Reconfigurable Intelligent Surfaces—0
Conditional Generation Using Polynomial ExpansionsCode0
SwiftSRGAN -- Rethinking Super-Resolution for Efficient and Real-time Inference—0
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction—0
Learning A 3D-CNN and Transformer Prior for Hyperspectral Image Super-Resolution—0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
Non-invasive hemodynamic analysis for aortic regurgitation using computational fluid dynamics and deep learning—0
Local-Selective Feature Distillation for Single Image Super-Resolution—0
FreqNet: A Frequency-domain Image Super-Resolution Network with Dicrete Cosine Transform—0
AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for Face Hallucination—0
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior—0
Resistance-Time Co-Modulated PointNet for Temporal Super-Resolution Simulation of Blood Vessel Flows—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Image Super-Resolution Using T-Tetromino Pixels—0
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution—0
Pixel-Level Kernel Estimation for Blind Super-ResolutionCode0
Small or Far Away? Exploiting Deep Super-Resolution and Altitude Data for Aerial Animal SurveillanceCode0
Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets—0
GDCA: GAN-based single image super resolution with Dual discriminators and Channel Attention—0
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process—0
Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation—0
Texture-enhanced Light Field Super-resolution with Spatio-Angular Decomposition KernelsCode0
Remote Sensing Image Super-resolution and Object Detection: Benchmark and State of the Art—0
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution—0
Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified