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 13261350 of 1589 papers

TitleStatusHype
Camera Lens Super-ResolutionCode0
Controlling Neural Networks via Energy Dissipation0
Deep Back-Projection Networks for Single Image Super-resolutionCode0
Lightweight Image Super-Resolution with Adaptive Weighted Learning NetworkCode0
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model0
PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study0
CFSNet: Toward a Controllable Feature Space for Image RestorationCode0
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
DeepRED: Deep Image Prior Powered by REDCode0
Recurrent Back-Projection Network for Video Super-ResolutionCode0
Feedback Network for Image Super-ResolutionCode0
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution NetworkCode0
A Matrix-in-matrix Neural Network for Image Super ResolutionCode0
Proximal Splitting Networks for Image Restoration0
Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution0
Learning Parallax Attention for Stereo Image Super-ResolutionCode0
Universally Slimmable Networks and Improved Training TechniquesCode0
Efficient Deep Neural Network for Photo-realistic Image Super-ResolutionCode0
Meta-SR: A Magnification-Arbitrary Network for Super-ResolutionCode1
Image Super-Resolution by Neural Texture TransferCode0
Deep Learning for Multiple-Image Super-ResolutionCode0
Generative Collaborative Networks for Single Image Super-ResolutionCode0
Hypernetwork functional image representation0
Deep Learning for Image Super-resolution: A SurveyCode0
Lightweight Feature Fusion Network for Single Image Super-ResolutionCode0
Show:102550
← PrevPage 54 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