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 431–440 of 3874 papers

TitleStatusHype
Compression-Aware Video Super-ResolutionCode1
Bayesian Image Super-Resolution with Deep Modeling of Image StatisticsCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-ResolutionCode1
Accelerating Diffusion Models for Inverse Problems through Shortcut SamplingCode1
Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and GeneralizabilityCode1
Deep Unfolding Network for Image Super-ResolutionCode1
Deep Unfolding Convolutional Dictionary Model for Multi-Contrast MRI Super-resolution and ReconstructionCode1
A Lightweight Recurrent Aggregation Network for Satellite Video Super-ResolutionCode1
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net DiscriminatorsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified