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 341–350 of 3874 papers

TitleStatusHype
Deep Blind Super-Resolution for Satellite VideoCode1
Deep Blind Video Super-resolutionCode1
Deep Diversity-Enhanced Feature Representation of Hyperspectral ImagesCode1
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-ResolutionCode1
Deep Image PriorCode1
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution NetworksCode1
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
A Spectral Diffusion Prior for Hyperspectral Image Super-ResolutionCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified