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 1861–1870 of 3874 papers

TitleStatusHype
Image Inpainting for High-Resolution Textures using CNN Texture Synthesis—0
Integrated Super-resolution Sensing and Symbiotic Communication with 3D Sparse MIMO for Low-Altitude UAV Swarm—0
Image inpainting for corrupted images by using the semi-super resolution GAN—0
Interactive Image Manipulation with Complex Text Instructions—0
Image Enhancement by Recurrently-trained Super-resolution Network—0
Deep Likelihood Network for Image Restoration with Multiple Degradation Levels—0
Interpretable Deep Multimodal Image Super-Resolution—0
Benchmarking Super-Resolution Algorithms on Real Data—0
Interpretable Super-Resolution via a Learned Time-Series Representation—0
Image Denoising and Super-Resolution using Residual Learning of Deep Convolutional Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified