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

Showing 10011025 of 1589 papers

TitleStatusHype
A Comprehensive Review of Deep Learning-based Single Image Super-resolution0
Selfie Periocular Verification using an Efficient Super-Resolution Approach0
A Generative Model for Hallucinating Diverse Versions of Super Resolution Images0
Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance imagesCode0
Deep learning architectural designs for super-resolution of noisy imagesCode1
Single Image Super-Resolution using Residual Channel Attention NetworkCode0
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity AttackCode1
I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling0
Real-World Super-Resolution of Face-Images from Surveillance Cameras0
Exploiting Raw Images for Real-Scene Super-ResolutionCode1
Deep Burst Super-ResolutionCode1
Proba-V-ref: Repurposing the Proba-V challenge for reference-aware super resolutionCode0
Quality Assessment of Super-Resolved Omnidirectional Image Quality Using Tangential Views0
Learning Structral coherence Via Generative Adversarial Network for Single Image Super-ResolutionCode1
3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstructionCode1
Progressive Image Super-Resolution via Neural Differential Equation0
GhostSR: Learning Ghost Features for Efficient Image Super-ResolutionCode0
Hyperspectral Image Super-Resolution with Spectral Mixup and Heterogeneous DatasetsCode1
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution0
Deep Learning-based Face Super-Resolution: A SurveyCode1
Single Image Super-Resolution0
More Reliable AI Solution: Breast Ultrasound Diagnosis Using Multi-AI Combination0
Dual-Stream Fusion Network for Spatiotemporal Video Super-ResolutionCode0
Transformers in Vision: A Survey0
Benchmarking Ultra-High-Definition Image Super-Resolution0
Show:102550
← PrevPage 41 of 64Next →

Benchmark Results

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