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 2101–2150 of 3874 papers

TitleStatusHype
Enhancing digital core image resolution using optimal upscaling algorithm: with application to paired SEM images—0
Enhancing Frequency for Single Image Super-Resolution with Learnable Separable Kernels—0
Enhancing Image Resolution: A Simulation Study and Sensitivity Analysis of System Parameters for Resourcesat-3S/3SA—0
Enhancing Multi-Scale Implicit Learning in Image Super-Resolution with Integrated Positional Encoding—0
Enhancing Perceptual Loss with Adversarial Feature Matching for Super-Resolution—0
Enhancing Quality of Pose-varied Face Restoration with Local Weak Feature Sensing and GAN Prior—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Enhancing Sentinel-2 Image Resolution: Evaluating Advanced Techniques based on Convolutional and Generative Neural Networks—0
Enhancing super-resolution ultrasound localisation through multi-frame deconvolution exploiting spatiotemporal coherence—0
Enhancing the Spatial Resolution of Stereo Images Using a Parallax Prior—0
Enhancing Traffic Scene Predictions with Generative Adversarial Networks—0
Enhancing Weather Predictions: Super-Resolution via Deep Diffusion Models—0
Ensemble Learning for Microbubble Localization in Super-Resolution Ultrasound—0
EPNet: An Efficient Pyramid Network for Enhanced Single-Image Super-Resolution with Reduced Computational Requirements—0
EPS: Efficient Patch Sampling for Video Overfitting in Deep Super-Resolution Model Training—0
EPSR: Edge Profile Super resolution—0
Equilibrium Conserving Neural Operators for Super-Resolution Learning—0
ERNet Family: Hardware-Oriented CNN Models for Computational Imaging Using Block-Based Inference—0
Error-correcting neural networks for semi-Lagrangian advection in the level-set method—0
ESC-MISR: Enhancing Spatial Correlations for Multi-Image Super-Resolution in Remote Sensing—0
ESRPCB: an Edge guided Super-Resolution model and Ensemble learning for tiny Printed Circuit Board Defect detection—0
ESSR: An 8K@30FPS Super-Resolution Accelerator With Edge Selective Network—0
ESTformer: Transformer Utilizing Spatiotemporal Dependencies for Electroencaphalogram Super-resolution—0
Estimates of maize plant density from UAV RGB images using Faster-RCNN detection model: impact of the spatial resolution—0
ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes—0
Evaluating Detection Thresholds: The Impact of False Positives and Negatives on Super-Resolution Ultrasound Localization Microscopy—0
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models—0
Evaluating the Adversarial Robustness for Fourier Neural Operators—0
Evaluating the Generalization Ability of Super-Resolution Networks—0
Evaluation of Machine-generated Biomedical Images via A Tally-based Similarity Measure—0
EventAid: Benchmarking Event-aided Image/Video Enhancement Algorithms with Real-captured Hybrid Dataset—0
Event-based Video Super-Resolution via State Space Models—0
Event Signal Filtering via Probability Flux Estimation—0
Event-Stream Super Resolution using Sigma-Delta Neural Network—0
Event Stream Super-Resolution via Spatiotemporal Constraint Learning—0
Every Pixel Tells a Story: End-to-End Urdu Newspaper OCR—0
EvIntSR-Net: Event Guided Multiple Latent Frames Reconstruction and Super-Resolution—0
EVRNet: Efficient Video Restoration on Edge Devices—0
Example-Based Modeling of Facial Texture From Deficient Data—0
Example-based super-resolution for point-cloud video—0
Expanding Synthetic Real-World Degradations for Blind Video Super Resolution—0
Expansion microscopy reveals neural circuit organization in genetic animal models—0
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions—0
Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets—0
Exploiting Digital Surface Models for Inferring Super-Resolution for Remotely Sensed Images—0
Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models—0
What's in the Image? Explorable Decoding of Compressed Images—0
Exploring Deep Learning Image Super-Resolution for Iris Recognition—0
Exploring Diffusion with Test-Time Training on Efficient Image Restoration—0
Exploring Multi-Scale Feature Propagation and Communication for Image Super Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified