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 2311–2320 of 3874 papers

TitleStatusHype
Gridless Parameter Estimation in Partly Calibrated Rectangular Arrays—0
Gridless Tomographic SAR Imaging Based on Accelerated Atomic Norm Minimization with Efficiency—0
Group-based Bi-Directional Recurrent Wavelet Neural Networks for Video Super-Resolution—0
Group Iterative Spectrum Thresholding for Super-Resolution Sparse Spectral Selection—0
Guided Frequency Loss for Image Restoration—0
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion—0
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution—0
Gull: A Generative Multifunctional Audio Codec—0
GUN: Gradual Upsampling Network for Single Image Super-Resolution—0
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified