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 11761200 of 1589 papers

TitleStatusHype
SRFeat: Single Image Super-Resolution with Feature Discrimination0
SR-GAN for SR-gamma: super resolution of photon calorimeter images at collider experiments0
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution0
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution0
SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging0
SRTGAN: Triplet Loss based Generative Adversarial Network for Real-World Super-Resolution0
SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network0
State-of-the-Art Transformer Models for Image Super-Resolution: Techniques, Challenges, and Applications0
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention0
StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation0
Stochastic Deep Restoration Priors for Imaging Inverse Problems0
Stroke-based Cyclic Amplifier: Image Super-Resolution at Arbitrary Ultra-Large Scales0
Structural Similarity in Deep Features: Image Quality Assessment Robust to Geometrically Disparate Reference0
Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning0
Structure Tensor Based Image Interpolation Method0
Exploiting Style and Attention in Real-World Super-Resolution0
Sub-Aperture Feature Adaptation in Single Image Super-resolution Model for Light Field Imaging0
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation0
Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs0
Super-NeRF: View-consistent Detail Generation for NeRF super-resolution0
Super-Resolved Image Perceptual Quality Improvement via Multi-Feature Discriminators0
Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images0
Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning0
Super-Resolution for Remote Sensing Imagery via the Coupling of a Variational Model and Deep Learning0
Super-resolution Guided Pore Detection for Fingerprint Recognition0
Show:102550
← PrevPage 48 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