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 3351–3400 of 3874 papers

TitleStatusHype
Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution—0
Residual Non-local Attention Networks for Image RestorationCode0
Feedback Network for Image Super-ResolutionCode0
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution NetworkCode0
A Matrix-in-matrix Neural Network for Image Super ResolutionCode0
Proximal Splitting Networks for Image Restoration—0
Learning Super-resolution 3D Segmentation of Plant Root MRI Images from Few Examples—0
Robust Super-Resolution GAN, with Manifold-based and Perception Loss—0
Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution—0
Learning Parallax Attention for Stereo Image Super-ResolutionCode0
Two-Stream Action Recognition-Oriented Video Super-ResolutionCode0
Universally Slimmable Networks and Improved Training TechniquesCode0
Efficient Deep Neural Network for Photo-realistic Image Super-ResolutionCode0
DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis—0
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs—0
Image Super-Resolution by Neural Texture TransferCode0
Meta-SR: A Magnification-Arbitrary Network for Super-ResolutionCode1
A Unified Neural Architecture for Instrumental Audio TasksCode0
Deep Learning for Multiple-Image Super-ResolutionCode0
Two-phase Hair Image Synthesis by Self-Enhancing Generative Model—0
Generative Collaborative Networks for Single Image Super-ResolutionCode0
Hypernetwork functional image representation—0
GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems—0
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation—0
Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization—0
Deep Learning for Image Super-resolution: A SurveyCode0
Lightweight Feature Fusion Network for Single Image Super-ResolutionCode0
Breaking the Spatio-Angular Trade-off for Light Field Super-Resolution via LSTM Modelling on Epipolar Plane Images—0
Super-Resolution of Brain MRI Images using Overcomplete Dictionaries and Nonlocal Similarity—0
Advances on CNN-based super-resolution of Sentinel-2 images—0
Progressive Generative Adversarial Networks for Medical Image Super resolution—0
DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth CompletionCode0
Deep Hyperspectral Prior: Denoising, Inpainting, Super-ResolutionCode0
Compressing GANs using Knowledge Distillation—0
Deep Learning for Inverse Problems: Bounds and Regularizers—0
Medical Image Super-Resolution Using a Generative Adversarial Network—0
Resolution enhancement in scanning electron microscopy using deep learning—0
TGAN: Deep Tensor Generative Adversarial Nets for Large Image GenerationCode0
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture SearchCode0
Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy—0
Single MR Image Super-Resolution via Channel Splitting and Serial Fusion Network—0
Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution—0
Generative Adversarial Classifier for Handwriting Characters Super-Resolution—0
Linearized ADMM and Fast Nonlocal Denoising for Efficient Plug-and-Play Restoration—0
How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale ApproachCode1
Detecting Overfitting of Deep Generative Networks via Latent RecoveryCode0
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational InferenceCode0
Image Super-Resolution as a Defense Against Adversarial AttacksCode0
Multi-Objective Reinforced Evolution in Mobile Neural Architecture SearchCode0
Sex-Classification from Cell-Phones Periocular Iris Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified