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 3351–3375 of 3874 papers

TitleStatusHype
Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR ApplicationsCode0
Super-Resolved Image Perceptual Quality Improvement via Multi-Feature Discriminators—0
Multi-scale deep neural networks for real image super-resolutionCode0
Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks—0
Deep Likelihood Network for Image Restoration with Multiple Degradation Levels—0
Feature Forwarding for Efficient Single Image DehazingCode0
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification LayersCode0
Process of image super-resolution—0
Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images—0
A Deep Journey into Super-resolution: A surveyCode0
MAANet: Multi-view Aware Attention Networks for Image Super-ResolutionCode0
Evaluating Robustness of Deep Image Super-Resolution against Adversarial AttacksCode0
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-NetworkCode0
Label Super Resolution with Inter-Instance Loss—0
Data-Driven Design for Fourier Ptychographic Microscopy—0
Camera Lens Super-ResolutionCode0
Blind Super-Resolution With Iterative Kernel CorrectionCode0
Controlling Neural Networks via Energy Dissipation—0
Fast Spatio-Temporal Residual Network for Video Super-Resolution—0
Lightweight Image Super-Resolution with Adaptive Weighted Learning NetworkCode0
Deep Back-Projection Networks for Single Image Super-resolutionCode0
Learning Implicit Generative Models by Matching Perceptual Features—0
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model—0
PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study—0
CFSNet: Toward a Controllable Feature Space for Image RestorationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified