SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 1651–1700 of 3874 papers

TitleStatusHype
Reference-based Image and Video Super-Resolution via C2-MatchingCode2
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends—0
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution—0
Meta-Learned Kernel For Blind Super-Resolution Kernel EstimationCode1
DCS-RISR: Dynamic Channel Splitting for Efficient Real-world Image Super-Resolution—0
Bi-Noising Diffusion: Towards Conditional Diffusion Models with Generative Restoration Priors—0
Mitigating Artifacts in Real-World Video Super-Resolution ModelsCode1
U2Net: A General Framework with Spatial-Spectral-Integrated Double U-Net for Image FusionCode1
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-ResolutionCode1
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering—0
Neural Volume Super-Resolution—0
On the Robustness of Normalizing Flows for Inverse Problems in Imaging—0
Spatio-Temporal Super-Resolution of Dynamical Systems using Physics-Informed Deep-Learning—0
A Scale-Arbitrary Image Super-Resolution Network Using Frequency-domain Information—0
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-ResolutionCode1
RainUNet for Super-Resolution Rain Movie Prediction under Spatio-temporal ShiftsCode1
Learning Continuous Depth Representation via Geometric Spatial AggregatorCode1
Super-resolution Probabilistic Rain Prediction from Satellite Data Using 3D U-Nets and EarthFormersCode1
ADIR: Adaptive Diffusion for Image Reconstruction—0
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast CompetitionCode0
Double U-Net for Super-Resolution and Segmentation of Live Cell Images—0
Learning Detail-Structure Alternative Optimization for Blind Super-ResolutionCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
DiTBN: Detail Injection-Based Two-Branch Network for Pansharpening of Remote Sensing ImagesCode0
Downscaling Extreme Rainfall Using Physical-Statistical Generative Adversarial Learning—0
Global Learnable Attention for Single Image Super-ResolutionCode1
Super-resolution of positive near-colliding point sources—0
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space ModelCode4
MrSARP: A Hierarchical Deep Generative Prior for SAR Image Super-resolution—0
Knowledge Distillation based Degradation Estimation for Blind Super-ResolutionCode1
Adaptive adversarial training method for improving multi-scale GAN based on generalization bound theory—0
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold—0
From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-ResolutionCode1
FREDSR: Fourier Residual Efficient Diffusive GAN for Single Image Super Resolution—0
Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantificationCode1
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution—0
A mathematical theory of super-resolution and two-point resolution—0
Separation-Free Spectral Super-Resolution via Convex Optimization—0
Synthetic Low-Field MRI Super-Resolution Via Nested U-Net Architecture—0
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems—0
Meet-in-the-middle: Multi-scale upsampling and matching for cross-resolution face recognition—0
Temporal Super-Resolution using Multi-Channel Illumination Source—0
Interactive Image Manipulation with Complex Text Instructions—0
Simulation-based parameter optimization for fetal brain MRI super-resolution reconstruction—0
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image SynthesisCode1
Domain generalization in fetal brain MRI segmentation \ multi-reconstruction augmentation—0
A mathematical theory of resolution limits for super-resolution of positive sources—0
Perception-Oriented Single Image Super-Resolution using Optimal Objective EstimationCode1
GAN Prior based Null-Space Learning for Consistent Super-ResolutionCode1
Immersive Neural Graphics PrimitivesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified