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

Showing 34513475 of 3874 papers

TitleStatusHype
A Generative Model for Hallucinating Diverse Versions of Super Resolution Images0
Supplementary Meta-Learning: Towards a Dynamic Model for Deep Neural Networks0
Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution0
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts0
Surf2CT: Cascaded 3D Flow Matching Models for Torso 3D CT Synthesis from Skin Surface0
Surface Geometry Processing: An Efficient Normal-based Detail Representation0
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets0
Surveillance Face Anti-spoofing0
A Generative Adversarial Network for AI-Aided Chair Design0
A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models0
A Generalized Tensor Formulation for Hyperspectral Image Super-Resolution Under General Spatial Blurring0
SwiftSRGAN -- Rethinking Super-Resolution for Efficient and Real-time Inference0
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery0
AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for Face Hallucination0
A full-resolution training framework for Sentinel-2 image fusion0
SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge0
A Frequency Domain Neural Network for Fast Image Super-resolution0
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution0
SwinRDM: Integrate SwinRNN with Diffusion Model towards High-Resolution and High-Quality Weather Forecasting0
A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames0
A Flow-based Truncated Denoising Diffusion Model for Super-resolution Magnetic Resonance Spectroscopic Imaging0
A Fast Text-Driven Approach for Generating Artistic Content0
A fast patch-dictionary method for whole image recovery0
SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis0
Synthesis of realistic fetal MRI with conditional Generative Adversarial Networks0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified