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 3401–3450 of 3874 papers

TitleStatusHype
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
Compressing GANs using Knowledge Distillation—0
Deep Hyperspectral Prior: Denoising, Inpainting, Super-ResolutionCode0
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
Generative Adversarial Classifier for Handwriting Characters Super-Resolution—0
Linearized ADMM and Fast Nonlocal Denoising for Efficient Plug-and-Play Restoration—0
Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution—0
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
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse CodingCode0
Brain MRI super-resolution using 3D generative adversarial networksCode0
Residual Dense Network for Image RestorationCode0
Perceptual deep depth super-resolutionCode0
Multi-Frame Super-Resolution Reconstruction with Applications to Medical Imaging—0
Multimodal Sensor Fusion In Single Thermal image Super-ResolutionCode0
3DSRnet: Video Super-resolution using 3D Convolutional Neural NetworksCode0
SREdgeNet: Edge Enhanced Single Image Super Resolution using Dense Edge Detection Network and Feature Merge Network—0
Efficient Super Resolution Using Binarized Neural Network—0
Advanced Super-Resolution using Lossless Pooling Convolutional Networks—0
Wider Channel Attention Network for Remote Sensing Image Super-resolution—0
Efficient Super Resolution For Large-Scale Images Using Attentional GAN—0
Unsupervised Degradation Learning for Single Image Super-Resolution—0
The Effects of Super-Resolution on Object Detection Performance in Satellite ImageryCode0
Supervised Deep Kriging for Single-Image Super-Resolution—0
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss—0
Binary Document Image Super Resolution for Improved Readability and OCR PerformanceCode0
Why Are Deep Representations Good Perceptual Quality Features?—0
Lightweight and Efficient Image Super-Resolution with Block State-based Recursive NetworkCode0
Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal LearningCode0
MAMNet: Multi-path Adaptive Modulation Network for Image Super-ResolutionCode0
Image Reconstruction with Predictive Filter FlowCode0
Patch-based Progressive 3D Point Set UpsamplingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified