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 651–700 of 1589 papers

TitleStatusHype
Fingerprints of Super Resolution Networks—0
Learning Optimal Combination Patterns for Lightweight Stereo Image Super-Resolution—0
Guidance Disentanglement Network for Optics-Guided Thermal UAV Image Super-ResolutionCode0
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
AdaDiffSR: Adaptive Region-aware Dynamic Acceleration Diffusion Model for Real-World Image Super-Resolution—0
ConsisSR: Delving Deep into Consistency in Diffusion-based Image Super-Resolution—0
Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution—0
HASN: Hybrid Attention Separable Network for Efficient Image Super-resolutionCode0
MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-ResolutionCode0
Stochastic Deep Restoration Priors for Imaging Inverse Problems—0
A Generalized Tensor Formulation for Hyperspectral Image Super-Resolution Under General Spatial Blurring—0
LGFN: Lightweight Light Field Image Super-Resolution using Local Convolution Modulation and Global Attention Feature Extraction—0
Unifying Dimensions: A Linear Adaptive Approach to Lightweight Image Super-ResolutionCode0
NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results—0
Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity CluesCode0
One Model for Two Tasks: Cooperatively Recognizing and Recovering Low-Resolution Scene Text Images by Iterative Mutual Guidance—0
Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring—0
Single-Layer Learnable Activation for Implicit Neural Representation (SL^2A-INR)—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
Learning Two-factor Representation for Magnetic Resonance Image Super-resolution—0
Test-time Training for Hyperspectral Image Super-resolution—0
Lightweight single-image super-resolution network based on dual paths—0
Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization ProblemCode0
Solving Video Inverse Problems Using Image Diffusion Models—0
SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution—0
HiTSR: A Hierarchical Transformer for Reference-based Super-ResolutionCode0
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment—0
ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral ImagesCode0
3D Photon Counting CT Image Super-Resolution Using Conditional Diffusion Model—0
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving TransformerCode0
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-ResolutionCode0
QMambaBSR: Burst Image Super-Resolution with Query State Space Model—0
DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution—0
Content-decoupled Contrastive Learning-based Implicit Degradation Modeling for Blind Image Super-Resolution—0
Kalman-Inspired Feature Propagation for Video Face Super-Resolution—0
Efficient Single Image Super-Resolution with Entropy Attention and Receptive Field Augmentation—0
Image Super-Resolution with Taylor Expansion Approximation and Large Field Reception—0
Sewer Image Super-Resolution with Depth Priors and Its Lightweight Network—0
GaussianSR: High Fidelity 2D Gaussian Splatting for Arbitrary-Scale Image Super-Resolution—0
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution—0
Efficient Multi-disparity Transformer for Light Field Image Super-resolution—0
UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt—0
Research on Image Super-Resolution Reconstruction Mechanism based on Convolutional Neural Network—0
Backdoor Attacks against Image-to-Image Networks—0
Task-driven single-image super-resolution reconstruction of document scans—0
Spatially-Variant Degradation Model for Dataset-free Super-resolutionCode0
UnmixingSR: Material-aware Network with Unsupervised Unmixing as Auxiliary Task for Hyperspectral Image Super-resolution—0
Deform-Mamba Network for MRI Super-Resolution—0
HiT-SR: Hierarchical Transformer for Efficient 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
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