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 1041–1050 of 3874 papers

TitleStatusHype
An efficient CNN for spectral reconstruction from RGB imagesCode1
Deep Image PriorCode1
Video Enhancement with Task-Oriented FlowCode1
Enhanced Deep Residual Networks for Single Image Super-ResolutionCode1
Recurrent Inference Machines for Solving Inverse ProblemsCode1
Face Super-Resolution Through Wasserstein GANsCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
Learned Spectral Super-ResolutionCode1
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural NetworkCode1
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial NetworkCode1
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified