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 3151–3200 of 3874 papers

TitleStatusHype
Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization—0
A deep learning framework for morphologic detail beyond the diffraction limit in infrared spectroscopic imagingCode0
Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics \& Losses—0
FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task LearningCode0
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties—0
AIM 2019 Challenge on Constrained Super-Resolution: Methods and ResultsCode0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
Training Set Effect on Super Resolution for Automated Target Recognition—0
Facial Expression Restoration Based on Improved Graph Convolutional Networks—0
Hyperspectral Super-resolution: A Coupled Nonnegative Block-term Tensor Decomposition Approach—0
Image Restoration Using Deep Regulated Convolutional NetworksCode0
Component Attention Guided Face Super-Resolution Network: CAGFaceCode0
Image Deconvolution with Deep Image and Kernel Priors—0
Multimodal Image Super-resolution via Deep Unfolding with Side Information—0
Translation position extracting in incoherent Fourier ptychography—0
ERNet Family: Hardware-Oriented CNN Models for Computational Imaging Using Block-Based Inference—0
eCNN: A Block-Based and Highly-Parallel CNN Accelerator for Edge Inference—0
Image Super-Resolution via Attention based Back Projection NetworksCode0
Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-ResolutionCode0
Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion—0
Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-ResolutionCode0
Unsupervised Image Super-Resolution with an Indirect Supervised Path—0
Image Super-Resolution Improved by Edge InformationCode0
High-dimensional Dense Residual Convolutional Neural Network for Light Field ReconstructionCode1
Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection—0
Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal CorrelationsCode0
Fast Image Restoration With Multi-Bin Trainable Linear UnitsCode0
Embedded Block Residual Network: A Recursive Restoration Model for Single-Image Super-Resolution—0
Deep Blind Hyperspectral Image Fusion—0
Kernel Modeling Super-Resolution on Real Low-Resolution ImagesCode0
Deep learning at scale for subgrid modeling in turbulent flows—0
Super-resolution photoacoustic and ultrasound imaging with sparse arrays—0
Unsupervised Projection Networks for Generative Adversarial Networks—0
Coarse-to-Fine Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes—0
Frame and Feature-Context Video Super-Resolution—0
Learning to Have an Ear for Face Super-Resolution—0
Multi-grained Attention Networks for Single Image Super-Resolution—0
Lightweight Image Super-Resolution with Information Multi-distillation NetworkCode1
Analysis and Interpretation of Deep CNN Representations as Perceptual Quality Features—0
Pixel Co-Occurence Based Loss Metrics for Super Resolution Texture Recovery—0
Relative Pixel Prediction For Autoregressive Image Generation—0
Manifold Modeling in Embedded Space: A Perspective for Interpreting "Deep Image Prior"—0
Efficient Residual Dense Block Search for Image Super-ResolutionCode0
Optimal Transport driven CycleGAN for Unsupervised Learning in Inverse Problems—0
Deformable Non-local Network for Video Super-ResolutionCode0
s-LWSR: Super Lightweight Super-Resolution NetworkCode0
Enhancing Traffic Scene Predictions with Generative Adversarial Networks—0
DRCAS: Deep Restoration Network for Hardware Based Compressive Acquisition Scheme—0
Unsupervised Learning for Real-World Super-Resolution—0
Underwater Image Super-Resolution using Deep Residual MultipliersCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified