SOTAVerified

Image Super-Resolution

Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.

Papers

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Showing 1151–1200 of 1589 papers

TitleStatusHype
Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral ImageryCode1
Enhancing Perceptual Loss with Adversarial Feature Matching for Super-Resolution—0
Invertible Image RescalingCode1
HiFaceGAN: Face Renovation via Collaborative Suppression and ReplenishmentCode1
Scene Text Image Super-Resolution in the WildCode1
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and ResultsCode1
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results—0
Neural Differential Equations for Single Image Super-resolution—0
Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction—0
GIMP-ML: Python Plugins for using Computer Vision Models in GIMP—0
Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoderCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution—0
ImagePairs: Realistic Super Resolution Dataset via Beam Splitter Camera Rig—0
Unified Dynamic Convolutional Network for Super-Resolution with Variational Degradations—0
D-SRGAN: DEM Super-Resolution with Generative Adversarial Networks—0
Image super-resolution reconstruction based on attention mechanism and feature fusion—0
Monte-Carlo Siamese Policy on Actor for Satellite Image Super Resolution—0
Learning A Single Network for Scale-Arbitrary Super-ResolutionCode1
Time accelerated image super-resolution using shallow residual feature representative network—0
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood EstimationCode1
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces—0
Robust Single-Image Super-Resolution via CNNs and TV-TV MinimizationCode1
Unsupervised Real-world Image Super Resolution via Domain-distance Aware TrainingCode1
Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New StrategyCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
Structure-Preserving Super Resolution with Gradient GuidanceCode1
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Learning regularization and intensity-gradient-based fidelity for single image super resolution—0
Deep Unfolding Network for Image Super-ResolutionCode1
Across-scale Process Similarity based Interpolation for Image Super-Resolution—0
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention—0
High-Resolution Daytime Translation Without Domain LabelsCode0
Weak Texture Information Map Guided Image Super-resolution with Deep Residual Networks—0
Closed-loop Matters: Dual Regression Networks for Single Image Super-ResolutionCode1
Stochastic Frequency Masking to Improve Super-Resolution and Denoising NetworksCode1
Hierarchical Neural Architecture Search for Single Image Super-ResolutionCode1
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative ModelsCode3
Perceptual Image Super-Resolution with Progressive Adversarial Network—0
Weighted Encoding Based Image Interpolation With Nonlocal Linear Regression Model—0
Creating High Resolution Images with a Latent Adversarial GeneratorCode1
Turbulence Enrichment using Physics-informed Generative Adversarial Networks—0
MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better—0
Gated Fusion Network for Degraded Image Super ResolutionCode1
Meta-Transfer Learning for Zero-Shot Super-ResolutionCode1
Super-Resolving Commercial Satellite Imagery Using Realistic Training Data—0
Unpaired Image Super-Resolution using Pseudo-SupervisionCode1
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All datasetsSet14 - 4x upscalingBSD100 - 4x upscalingUrban100 - 4x upscalingManga109 - 4x upscalingSet5 - 2x upscalingSet14 - 2x upscalingSet5 - 3x upscalingBSD100 - 2x upscalingUrban100 - 2x upscalingSet14 - 3x upscalingUrban100 - 3x upscalingBSD100 - 3x upscaling

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR29.54—Unverified
2HMA†PSNR29.51—Unverified
3Hi-IR-LPSNR29.49—Unverified
4HAT-LPSNR29.47—Unverified
5HAT_FIRPSNR29.44—Unverified
6DRCTPSNR29.4—Unverified
7HATPSNR29.38—Unverified
8CPAT+PSNR29.36—Unverified
9SwinFIRPSNR29.36—Unverified
10CPATPSNR29.34—Unverified
#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR28.16—Unverified
2HMA†PSNR28.13—Unverified
3Hi-IR-LPSNR28.13—Unverified
4HAT-LPSNR28.09—Unverified
5HAT_FIRPSNR28.07—Unverified
6CPAT+PSNR28.06—Unverified
7DRCTPSNR28.06—Unverified
8HATPSNR28.05—Unverified
9CPATPSNR28.04—Unverified
10SwinFIRPSNR28.03—Unverified
#ModelMetricClaimedVerifiedStatus
1Hi-IR-LPSNR28.72—Unverified
2DRCT-LPSNR28.7—Unverified
3HMA†PSNR28.69—Unverified
4HAT-LPSNR28.6—Unverified
5HAT_FIRPSNR28.43—Unverified
6DRCTPSNR28.4—Unverified
7HATPSNR28.37—Unverified
8CPAT+PSNR28.33—Unverified
9CPATPSNR28.22—Unverified
10PFTPSNR28.2—Unverified