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 526550 of 1589 papers

TitleStatusHype
Efficient CNN-based Super Resolution Algorithms for mmWave Mobile Radar ImagingCode1
Bicubic++: Slim, Slimmer, Slimmest -- Designing an Industry-Grade Super-Resolution NetworkCode2
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-ResolutionCode1
Super-NeRF: View-consistent Detail Generation for NeRF super-resolution0
OPDN: Omnidirectional Position-aware Deformable Network for Omnidirectional Image Super-Resolution0
SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge0
Ultra Sharp : Study of Single Image Super Resolution using Residual Dense NetworkCode0
Omni Aggregation Networks for Lightweight Image Super-ResolutionCode2
NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and ResultsCode1
Quantum Annealing for Single Image Super-Resolution0
DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution0
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B ImageryCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
Cross-View Hierarchy Network for Stereo Image Super-ResolutionCode1
Hyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution0
Towards Arbitrary-scale Histopathology Image Super-resolution: An Efficient Dual-branch Framework based on Implicit Self-texture Enhancement0
Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-ResolutionCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation TransformerCode1
Image-to-image domain adaptation for vehicle re-identification0
Dual Circle Contrastive Learning-Based Blind Image Super-Resolution0
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-ResolutionCode0
Random Weights Networks Work as Loss Prior Constraint for Image Restoration0
Implicit Diffusion Models for Continuous Super-ResolutionCode2
Show:102550
← PrevPage 22 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