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 2101–2125 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
Show:102550
← PrevPage 85 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified