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 3251–3300 of 3874 papers

TitleStatusHype
SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution—0
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
All-in-One Deep Learning Framework for MR Image Reconstruction—0
Video Super Resolution Based on Deep Learning: A Comprehensive Survey—0
STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution—0
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution—0
Fast and Accurate: Video Enhancement using Sparse Depth—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
State-of-the-Art Transformer Models for Image Super-Resolution: Techniques, Challenges, and Applications—0
Regional climate risk assessment from climate models using probabilistic machine learning—0
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts—0
Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales—0
Imitating the Functionality of Image-to-Image Models Using a Single Example—0
Video super-resolution for single-photon LIDAR—0
Steered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoising—0
Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention—0
Stereo Image Rain Removal via Dual-View Mutual Attention—0
StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation—0
Stochastic Attribute Modeling for Face Super-Resolution—0
Stochastic Deep Restoration Priors for Imaging Inverse Problems—0
A learning-based view extrapolation method for axial super-resolution—0
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution—0
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser—0
A Joint Intensity and Depth Co-Sparse Analysis Model for Depth Map Super-Resolution—0
Stochastic Super-Resolution For Gaussian Textures—0
Stochastic super-resolution for Gaussian microtextures—0
Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models—0
3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution—0
Stop-and-go wave super-resolution reconstruction via iterative refinement—0
3D Super-Resolution Ultrasound with Adaptive Weight-Based Beamforming—0
AI Techniques for Cone Beam Computed Tomography in Dentistry: Trends and Practices—0
Stroke-based Cyclic Amplifier: Image Super-Resolution at Arbitrary Ultra-Large Scales—0
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends—0
Structural Similarity in Deep Features: Image Quality Assessment Robust to Geometrically Disparate Reference—0
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results—0
AIM 2024 Challenge on Efficient Video Super-Resolution for AV1 Compressed Content—0
Structured Bayesian Gaussian process latent variable model—0
Structured illumination microscopy for dual-modality 3D sub-diffraction resolution fluorescence and refractive-index reconstruction—0
Video Super-Resolution Using a Grouped Residual in Residual Network—0
Structure Flow-Guided Network for Real Depth Super-Resolution—0
Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning—0
AIM 2020 Challenge on Video Temporal Super-Resolution—0
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results—0
Structure Tensor Based Image Interpolation Method—0
Studying Very Low Resolution Recognition Using Deep Networks—0
Study of Subjective and Objective Quality in Super-Resolution Enhanced Broadcast Images on a Novel SR-IQA Dataset—0
Exploiting Style and Attention in Real-World Super-Resolution—0
StyleDEM: a Versatile Model for Authoring Terrains—0
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results—0
StyleGAN-induced data-driven regularization for inverse problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified