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 3701–3725 of 3874 papers

TitleStatusHype
Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network—0
Volumetric Super-Resolution of Multispectral Data—0
Signal reconstruction via operator guiding—0
Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding—0
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGACode0
Super-Resolution of Wavelet-Encoded Images—0
Regularized Residual Quantization: a multi-layer sparse dictionary learning approach—0
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution—0
Sub-Pixel Registration of Wavelet-Encoded Images—0
A Nuclear-norm Model for Multi-Frame Super-Resolution Reconstruction from Video Clips—0
Single Image Super-Resolution based on Wiener Filter in Similarity Domain—0
Deep Laplacian Pyramid Networks for Fast and Accurate Super-ResolutionCode0
Detail-revealing Deep Video Super-resolutionCode0
Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data—0
Isotropic reconstruction of 3D fluorescence microscopy images using convolutional neural networks—0
Single Image Super Resolution - When Model Adaptation Matters—0
Image Restoration using Autoencoding Priors—0
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection ModelsCode0
Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network—0
Effect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild—0
Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction—0
Convolutional Low-Resolution Fine-Grained Classification—0
GUN: Gradual Upsampling Network for Single Image Super-Resolution—0
Local Patch Encoding-Based Method for Single Image Super-Resolution—0
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified