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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3061–3070 of 3874 papers

TitleStatusHype
Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual PerceptionCode1
Multiple Angles of Arrival Estimation using Neural Networks—0
Super-resolution of multispectral satellite images using convolutional neural networks—0
Large Hole Image Inpainting With Compress-Decompression Network—0
A Generative Adversarial Network for AI-Aided Chair Design—0
Learning Deep Analysis Dictionaries -- Part II: Convolutional Dictionaries—0
Learning Deep Analysis Dictionaries for Image Super-Resolution—0
Sound field reconstruction in rooms: inpainting meets super-resolutionCode1
Optimizing Generative Adversarial Networks for Image Super Resolution via Latent Space Regularization—0
Computational resolution limit: a theory towards super-resolution—0
Show:102550
← PrevPage 307 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified