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

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Showing 801–850 of 1589 papers

TitleStatusHype
Blind Image Super-resolution with Rich Texture-Aware Codebooks—0
Local Statistics for Generative Image Detection—0
Unpaired MRI Super Resolution with Contrastive Learning—0
PTSR: Patch Translator for Image Super-Resolution—0
Multi-granularity Backprojection Transformer for Remote Sensing Image Super-Resolution—0
Video Super-Resolution Using a Grouped Residual in Residual Network—0
Learning Many-to-Many Mapping for Unpaired Real-World Image Super-resolution and Downscaling—0
Deep learning-based image super-resolution of a novel end-expandable optical fiber probe for application in esophageal cancer diagnostics—0
EXTRACTER: Efficient Texture Matching with Attention and Gradient Enhancing for Large Scale Image Super ResolutionCode0
Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image SynthesisCode0
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis—0
Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN—0
Data Upcycling Knowledge Distillation for Image Super-ResolutionCode0
Adaptation of the super resolution SOTA for Art Restoration in camera capture imagesCode0
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinementCode0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
License Plate Super-Resolution Using Diffusion Models—0
Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool—0
RGB-Guided Resolution Enhancement of IR Images—0
SR-GAN for SR-gamma: super resolution of photon calorimeter images at collider experiments—0
Dynamic Attention-Guided Diffusion for Image Super-Resolution—0
CMISR: Circular Medical Image Super-Resolution—0
On Versatile Video Coding at UHD with Machine-Learning-Based Super-Resolution—0
Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment TechnologyCode0
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution—0
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution—0
NLCUnet: Single-Image Super-Resolution Network with Hairline Details—0
PartDiff: Image Super-resolution with Partial Diffusion Models—0
Frequency-aware optical coherence tomography image super-resolution via conditional generative adversarial neural network—0
A comparative analysis of SRGAN models—0
Soft-IntroVAE for Continuous Latent space Image Super-Resolution—0
MaxSR: Image Super-Resolution Using Improved MaxViT—0
DWA: Differential Wavelet Amplifier for Image Super-ResolutionCode0
Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution—0
Compound Attention and Neighbor Matching Network for Multi-contrast MRI Super-resolution—0
Spatio-Temporal Perception-Distortion Trade-off in Learned Video SRCode0
ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution—0
SPDER: Semiperiodic Damping-Enabled Object Representation—0
Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging SystemsCode0
Semantic Segmentation Using Super Resolution Technique as Pre-Processing—0
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling—0
HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Optical Coherence Tomography Image Enhancement via Block Hankelization and Low Rank Tensor Network Approximation—0
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models—0
Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration—0
A Unified Framework to Super-Resolve Face Images of Varied Low Resolutions—0
Scale Guided Hypernetwork for Blind Super-Resolution Image Quality AssessmentCode0
EfficientSRFace: An Efficient Network with Super-Resolution Enhancement for Accurate Face Detection—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
8CPAT+PSNR29.36—Unverified
9SwinFIRPSNR29.36—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