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 2951–2975 of 3874 papers

TitleStatusHype
Unsupervised Video Understanding by Reconciliation of Posture Similarities—0
Untrained, physics-informed neural networks for structured illumination microscopy—0
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution—0
Urban precipitation downscaling using deep learning: a smart city application over Austin, Texas, USA—0
Use of triplet loss for facial restoration in low-resolution images—0
USF Spectral Estimation: Prevalence of Gaussian Cramér-Rao Bounds Despite Modulo Folding—0
USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution—0
Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows—0
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology—0
Using Super-Resolution Imaging for Recognition of Low-Resolution Blurred License Plates: A Comparative Study of Real-ESRGAN, A-ESRGAN, and StarSRGAN—0
V2X Sidelink Positioning in FR1: From Ray-Tracing and Channel Estimation to Bayesian Tracking—0
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals—0
VarSR: Variational Super-Resolution Network for Very Low Resolution Images—0
VEnhancer: Generative Space-Time Enhancement for Video Generation—0
Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network—0
Very Deep Super-Resolution of Remotely Sensed Images with Mean Square Error and Var-norm Estimators as Loss Functions—0
Very Low-Resolution Iris Recognition Via Eigen-Patch Super-Resolution and Matcher Fusion—0
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge—0
VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution—0
VHS to HDTV Video Translation using Multi-task Adversarial Learning—0
Video compression with low complexity CNN-based spatial resolution adaptation—0
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements—0
Video-Specific Autoencoders for Exploring, Editing and Transmitting Videos—0
Video Face Super-Resolution with Motion-Adaptive Feedback Cell—0
VideoGigaGAN: Towards Detail-rich Video Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified