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 1321–1330 of 3874 papers

TitleStatusHype
AIM 2024 Challenge on Efficient Video Super-Resolution for AV1 Compressed Content—0
Deep Image Super Resolution via Natural Image Priors—0
Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy—0
GAN-based Super-Resolution and Segmentation of Retinal Layers in Optical coherence tomography Scans—0
A Wideband Distributed Massive MIMO Channel Sounder for Communication and Sensing—0
Deep Hierarchical Super Resolution for Scientific Data—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
Deep generative model super-resolves spatially correlated multiregional climate data—0
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
Adaptive Blind Super-Resolution Network for Spatial-Specific and Spatial-Agnostic Degradations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified