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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3476–3500 of 3874 papers

TitleStatusHype
Camera Lens Super-ResolutionCode0
PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-ResolutionCode0
Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception ModuleCode0
C2PD: Continuity-Constrained Pixelwise Deformation for Guided Depth Super-ResolutionCode0
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected NetworkCode0
Photometric Depth Super-ResolutionCode0
Super-Resolution using Convolutional Neural Networks without Any Checkerboard ArtifactsCode0
Efficient Deep Neural Network for Photo-realistic Image Super-ResolutionCode0
Learning to Super Resolve Intensity Images from EventsCode0
Adaptive Densely Connected Super-Resolution ReconstructionCode0
Deep Decomposition Learning for Inverse Imaging ProblemsCode0
Brain MRI super-resolution using 3D generative adversarial networksCode0
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical SystemsCode0
A Lightweight Recurrent Grouping Attention Network for Video Super-ResolutionCode0
Learning Series-Parallel Lookup Tables for Efficient Image Super-ResolutionCode0
Physics-Informed Ensemble Representation for Light-Field Image Super-ResolutionCode0
Towards Representation Learning for Atmospheric DynamicsCode0
Learning Parallax Attention for Stereo Image Super-ResolutionCode0
Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-ResolutionCode0
Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer LearningCode0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Towards Super-Resolution CEST MRI for Visualization of Small StructuresCode0
Edge-Informed Single Image Super-ResolutionCode0
Super-Resolution with Deep Convolutional Sufficient StatisticsCode0
SinSR: Diffusion-Based Image Super-Resolution in a Single StepCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified