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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2226–2250 of 3874 papers

TitleStatusHype
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration—0
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid NetworkCode0
Large-scale single-photon imaging—0
Single-Image Super-Resolution Reconstruction based on the Differences of Neighboring Pixels—0
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images—0
Continual Learning Approaches for Anomaly DetectionCode0
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach—0
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
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
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
ADIR: Adaptive Diffusion for Image Reconstruction—0
Double U-Net for Super-Resolution and Segmentation of Live Cell Images—0
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast CompetitionCode0
Downscaling Extreme Rainfall Using Physical-Statistical Generative Adversarial Learning—0
DiTBN: Detail Injection-Based Two-Branch Network for Pansharpening of Remote Sensing ImagesCode0
Super-resolution of positive near-colliding point sources—0
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold—0
Adaptive adversarial training method for improving multi-scale GAN based on generalization bound theory—0
MrSARP: A Hierarchical Deep Generative Prior for SAR Image Super-resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified