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

Showing 36263650 of 3874 papers

TitleStatusHype
Image Super-resolution via Feature-augmented Random ForestCode0
A Frequency Domain Neural Network for Fast Image Super-resolution0
Image Inpainting for High-Resolution Textures using CNN Texture Synthesis0
Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs0
Deep Sampling Networks0
InverseNet: Solving Inverse Problems with Splitting Networks0
FSRNet: End-to-End Learning Face Super-Resolution with Facial PriorsCode0
BLADE: Filter Learning for General Purpose Computational Photography0
Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning0
xUnit: Learning a Spatial Activation Function for Efficient Image RestorationCode0
The Perception-Distortion TradeoffCode0
Deep Inception-Residual Laplacian Pyramid Networks for Accurate Single Image Super-Resolution0
CT-SRCNN: Cascade Trained and Trimmed Deep Convolutional Neural Networks for Image Super Resolution0
Remote Sensing Image Fusion Based on Two-stream Fusion NetworkCode0
Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization0
Single Image Super-Resolution Using Lightweight CNN with Maxout Units0
ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network0
Separation-Free Super-Resolution from Compressed Measurements is Possible: an Orthonormal Atomic Norm Minimization Approach0
Accelerating GMM-based patch priors for image restoration: Three ingredients for a 100 speed-up0
Generative Adversarial Networks: An OverviewCode0
Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution0
A Review of Convolutional Neural Networks for Inverse Problems in ImagingCode0
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition0
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid NetworksCode0
Blind Image Fusion for Hyperspectral Imaging with the Directional Total VariationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified