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 2481–2490 of 3874 papers

TitleStatusHype
GHM Wavelet Transform for Deep Image Super Resolution—0
Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography—0
Super Resolution for Turbulent Flows in 2D: Stabilized Physics Informed Neural Networks—0
Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris—0
Denoiser-based projections for 2-D super-resolution multi-reference alignmentCode0
HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area SurveillanceCode0
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning—0
Dynamic super-resolution in particle tracking problems—0
Evaluating the Adversarial Robustness for Fourier Neural Operators—0
Dynamic Non-Regular Sampling Sensor Using Frequency Selective Reconstruction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified