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 951–1000 of 1589 papers

TitleStatusHype
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
Permutation invariance and uncertainty in multitemporal image super-resolutionCode1
High-Frequency aware Perceptual Image Enhancement—0
Towards Compact Single Image Super-Resolution via Contrastive Self-distillationCode1
MIASSR: An Approach for Medical Image Arbitrary Scale Super-ResolutionCode1
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and BeyondCode1
Anchor-based Plain Net for Mobile Image Super-ResolutionCode1
Content-adaptive Representation Learning for Fast Image Super-resolution—0
XCycles Backprojection Acoustic Super-Resolution—0
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: ReportCode1
Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical NaturalnessCode1
A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution—0
EDPN: Enhanced Deep Pyramid Network for Blurry Image RestorationCode1
DPSRGAN: Dilation Patch Super-Resolution Generative Adversarial NetworksCode0
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-ResolutionCode1
Infrared Image Super-Resolution via Transfer Learning and PSRGANCode1
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain ConnectivityCode1
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic ModelsCode1
SRWarp: Generalized Image Super-Resolution under Arbitrary TransformationCode1
A Two-Stage Attentive Network for Single Image Super-ResolutionCode1
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution—0
Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic IndexesCode0
Neural Architecture Search for Image Super-Resolution Using Densely Constructed Search Space: DeCoNAS—0
Kernel Adversarial Learning for Real-world Image Super-resolution—0
Attention in Attention Network for Image Super-ResolutionCode1
Image Super-Resolution via Iterative RefinementCode1
BAM: A Balanced Attention Mechanism for Single Image Super ResolutionCode1
SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging—0
Conditional Hyper-Network for Blind Super-Resolution with Multiple DegradationsCode1
Flow-based Kernel Prior with Application to Blind Super-ResolutionCode1
Best-Buddy GANs for Highly Detailed Image Super-ResolutionCode1
Training a Task-Specific Image Reconstruction Loss—0
D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-ResolutionCode1
Asymmetric CNN for image super-resolutionCode1
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
Lightweight Image Super-Resolution with Multi-scale Feature Interaction Network—0
A new public Alsat-2B dataset for single-image super-resolutionCode1
Hyperspectral Image Super-Resolution in Arbitrary Input-Output Band Settings—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Self-Supervised Adaptation for Video Super-ResolutionCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation—0
Learning Frequency-aware Dynamic Network for Efficient Super-Resolution—0
D2C-SR: A Divergence to Convergence Approach for Image Super-Resolution—0
Feedback Refined Local-Global Network for Super-Resolution of Hyperspectral ImageryCode0
Real-World Single Image Super-Resolution: A Brief ReviewCode1
Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution EnhancementCode1
ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning—0
Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution—0
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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