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 1771–1780 of 3874 papers

TitleStatusHype
3D Volumetric Super-Resolution in Radiology Using 3D RRDB-GAN—0
Hybrid Neural Representations for Spherical Data—0
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography—0
Diffusion-based Light Field Synthesis—0
Fully Data-Driven Model for Increasing Sampling Rate Frequency of Seismic Data using Super-Resolution Generative Adversarial Networks—0
Improving Object Detection Quality in Football Through Super-Resolution Techniques—0
Spatial-and-Frequency-aware Restoration method for Images based on Diffusion Models—0
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow—0
You Only Need One Step: Fast Super-Resolution with Stable Diffusion via Scale Distillation—0
Reconfigurable AI Modules Aided Channel Estimation and MIMO Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified