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 33513375 of 3874 papers

TitleStatusHype
Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution0
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 Restoration0
Learning Super-resolution 3D Segmentation of Plant Root MRI Images from Few Examples0
Robust Super-Resolution GAN, with Manifold-based and Perception Loss0
Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution0
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 Synthesis0
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs0
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 Model0
Generative Collaborative Networks for Single Image Super-ResolutionCode0
Hypernetwork functional image representation0
GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems0
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation0
Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified