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 1001–1050 of 1589 papers

TitleStatusHype
Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution—0
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images—0
Transformers in Vision: A Survey—0
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution—0
Multimodal-Boost: Multimodal Medical Image Super-Resolution using Multi-Attention Network with Wavelet Transform—0
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing—0
Multimodal Deep Unfolding for Guided Image Super-Resolution—0
Multimodal Image Super-resolution via Deep Unfolding with Side Information—0
Adaptive Loss Function for Super Resolution Neural Networks Using Convex Optimization Techniques—0
DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution—0
Transport-based analysis, modeling, and learning from signal and data distributions—0
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics—0
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution—0
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach—0
Differentiable Search for Finding Optimal Quantization Strategy—0
Triple Attention Mixed Link Network for Single Image Super Resolution—0
Multi-Scale Feature Fusion using Channel Transformers for Guided Thermal Image Super Resolution—0
Multi-scale Image Super Resolution with a Single Auto-Regressive Model—0
Multi-Scale Progressive Fusion Learning for Depth Map Super-Resolution—0
XCAT -- Lightweight Quantized Single Image Super-Resolution using Heterogeneous Group Convolutions and Cross Concatenation—0
Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation—0
Differentiable Channel Sparsity Search via Weight Sharing within Filters—0
Hypernetwork functional image representation—0
Trustworthy SR: Resolving Ambiguity in Image Super-resolution via Diffusion Models and Human Feedback—0
Diff-Ensembler: Learning to Ensemble 2D Diffusion Models for Volume-to-Volume Medical Image Translation—0
Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network—0
DifAugGAN: A Practical Diffusion-style Data Augmentation for GAN-based Single Image Super-resolution—0
TSP-Mamba: The Travelling Salesman Problem Meets Mamba for Image Super-resolution and Beyond—0
Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution—0
Adaptive Dropout: Unleashing Dropout across Layers for Generalizable Image Super-Resolution—0
Neural Architecture Search for Image Super-Resolution Using Densely Constructed Search Space: DeCoNAS—0
Neural Differential Equations for Single Image Super-resolution—0
Deterministic Medical Image Translation via High-fidelity Brownian Bridges—0
Adaptive adversarial training method for improving multi-scale GAN based on generalization bound theory—0
Detail-Enhancing Framework for Reference-Based Image Super-Resolution—0
Depth Super Resolution by Rigid Body Self-Similarity in 3D—0
Dense U-net for super-resolution with shuffle pooling layer—0
Turbulence Enrichment using Physics-informed Generative Adversarial Networks—0
Densely Connected High Order Residual Network for Single Frame Image Super Resolution—0
NLCUnet: Single-Image Super-Resolution Network with Hairline Details—0
No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy—0
Dense Dual-Attention Network for Light Field Image Super-Resolution—0
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution—0
not-so-big-GAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt—0
NSD-DIL: Null-Shot Deblurring Using Deep Identity Learning—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results—0
Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild—0
Show:102550
← PrevPage 21 of 32Next →
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