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 2711–2720 of 3874 papers

TitleStatusHype
Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine—0
Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris—0
Super Resolution for Turbulent Flows in 2D: Stabilized Physics Informed Neural Networks—0
Super-resolution Guided Pore Detection for Fingerprint Recognition—0
Super-Resolution Harmonic Retrieval of Non-Circular Signals—0
Super-resolution image display using diffractive decoders—0
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN—0
Super Resolution image reconstructs via total variation-based image deconvolution: a majorization-minimization approach—0
Super-resolution imaging using super-oscillatory diffractive neural networks—0
Super-resolution in disordered media using neural networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified