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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1589 of 1589 papers

TitleStatusHype
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
Image Super-Resolution using Explicit Perceptual Loss—0
Image Superresolution using Scale-Recurrent Dense Network—0
Image Super-Resolution Using T-Tetromino Pixels—0
Image Super-Resolution Using VDSR-ResNeXt and SRCGAN—0
Feedback Pyramid Attention Networks for Single Image Super-Resolution—0
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model—0
Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy—0
Weak Texture Information Map Guided Image Super-resolution with Deep Residual Networks—0
Toward Real-World Super-Resolution via Adaptive Downsampling Models—0
Towards Arbitrary-scale Histopathology Image Super-resolution: An Efficient Dual-branch Framework based on Implicit Self-texture Enhancement—0
Feedback Neural Network based Super-resolution of DEM for generating high fidelity features—0
An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution—0
Federated Learning for Blind Image Super-Resolution—0
Feature Super-Resolution: Make Machine See More Clearly—0
Perception-oriented Single Image Super-Resolution via Dual Relativistic Average Generative Adversarial Networks—0
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence—0
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces—0
Feature Representation Matters: End-to-End Learning for Reference-based Image Super-resolution—0
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution—0
Image Super-Resolution With Deep Variational Autoencoders—0
Image Super-Resolution with Guarantees via Conformalized Generative Models—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Image-to-image domain adaptation for vehicle re-identification—0
Image Transformer—0
IMDeception: Grouped Information Distilling Super-Resolution Network—0
Fast single image super-resolution based on sigmoid transformation—0
Impact of deep learning-based image super-resolution on binary signal detection—0
Fast Single Image Super-Resolution—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Implicit Neural Representation Learning for Hyperspectral Image Super-Resolution—0
Improved Super-Resolution Convolution Neural Network for Large Images—0
Improved Super Resolution of MR Images Using CNNs and Vision Transformers—0
Improving Clinical Diagnosis Performance with Automated X-ray Scan Quality Enhancement Algorithms—0
Improving Generative Adversarial Networks for Video Super-Resolution—0
Fast Image Super-Resolution Based on In-Place Example Regression—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
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All datasetsSet14 - 4x upscalingBSD100 - 4x upscalingUrban100 - 4x upscalingManga109 - 4x upscalingSet5 - 2x upscalingSet14 - 2x upscalingSet5 - 3x upscalingBSD100 - 2x upscalingUrban100 - 2x upscalingSet14 - 3x upscalingUrban100 - 3x upscalingBSD100 - 3x upscaling

Benchmark Results

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