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 176200 of 1589 papers

TitleStatusHype
Cylin-Painting: Seamless 360 Panoramic Image Outpainting and BeyondCode1
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
Adaptive Patch Exiting for Scalable Single Image Super-ResolutionCode1
EDPN: Enhanced Deep Pyramid Network for Blurry Image RestorationCode1
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural RepresentationCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
Efficient CNN-based Super Resolution Algorithms for mmWave Mobile Radar ImagingCode1
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
Blockwise Parallel Decoding for Deep Autoregressive ModelsCode1
Blueprint Separable Residual Network for Efficient Image Super-ResolutionCode1
Cross-View Hierarchy Network for Stereo Image Super-ResolutionCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time seriesCode1
CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-ResolutionCode1
Physics Driven Deep Retinex Fusion for Adaptive Infrared and Visible Image FusionCode1
A New Dataset and Framework for Real-World Blurred Images Super-ResolutionCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Cross-receptive Focused Inference Network for Lightweight Image Super-ResolutionCode1
A New Dataset and Transformer for Stereoscopic Video Super-ResolutionCode1
A new public Alsat-2B dataset for single-image super-resolutionCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolutionCode1
Cross-Scale Internal Graph Neural Network for Image Super-ResolutionCode1
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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