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 2701–2725 of 3874 papers

TitleStatusHype
Privacy-Preserving Human Activity Recognition from Extreme Low Resolution—0
Private Eye: On the Limits of Textual Screen Peeking via Eyeglass Reflections in Video Conferencing—0
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI—0
Precipitation Downscaling with Spatiotemporal Video Diffusion—0
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties—0
An Optimal Transport Perspective on Unpaired Image Super-Resolution—0
Process of image super-resolution—0
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Unpaired MRI Super Resolution with Contrastive Learning—0
Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization—0
Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN—0
Progressive Generative Adversarial Networks for Medical Image Super resolution—0
Progressively Unfreezing Perceptual GAN—0
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution—0
Unstructured Road Vanishing Point Detection Using the Convolutional Neural Network and Heatmap Regression—0
Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches—0
Accurate super-resolution low-field brain MRI—0
Prompt-tuning latent diffusion models for inverse problems—0
Propagation Modeling for Physically Large Arrays: Measurements and Multipath Component Visibility—0
Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solving—0
Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks—0
Provable Compressed Sensing with Generative Priors via Langevin Dynamics—0
Unsupervised Alternating Optimization for Blind Hyperspectral Imagery Super-resolution—0
PINNs for Medical Image Analysis: A Survey—0
BLADE: Filter Learning for General Purpose Computational Photography—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified