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 501–525 of 3874 papers

TitleStatusHype
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural RepresentationCode1
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS DataCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-ResolutionCode1
Interpretable Detail-Fidelity Attention Network for Single Image Super-ResolutionCode1
InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion ModelCode1
Adversarial Magnification to Deceive Deepfake Detection through Super ResolutionCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Boosting Video Super Resolution with Patch-Based Temporal Redundancy OptimizationCode1
3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstructionCode1
Deep Learning-based Face Super-Resolution: A SurveyCode1
Deep Learning-Driven Ultra-High-Definition Image Restoration: A SurveyCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
Deep Image PriorCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
Deep Burst Super-ResolutionCode1
Burst Super-Resolution with Diffusion Models for Improving Perceptual QualityCode1
Deep Blind Video Super-resolutionCode1
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified