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 2301–2310 of 3874 papers

TitleStatusHype
Real-time, low-cost multi-person 3D pose estimation—0
Game Theory for Adversarial Attacks and DefensesCode0
Burst Image Restoration and EnhancementCode1
Gradient Step Denoiser for convergent Plug-and-PlayCode1
StyleGAN-induced data-driven regularization for inverse problems—0
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student LearningCode0
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and SynthesisCode0
ParaDiS: Parallelly Distributable Slimmable Neural Networks—0
Enhancement of Anime Imaging Enlargement using Modified Super-Resolution CNNCode1
An investigation of pre-upsampling generative modelling and Generative Adversarial Networks in audio super resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified