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 1601–1610 of 3874 papers

TitleStatusHype
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGACode0
HPRN: Holistic Prior-embedded Relation Network for Spectral Super-ResolutionCode0
HR-INR: Continuous Space-Time Video Super-Resolution via Event CameraCode0
Image Formation Model Guided Deep Image Super-ResolutionCode0
High-throughput, high-resolution registration-free generated adversarial network microscopyCode0
DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopyCode0
High-Resolution GAN Inversion for Degraded Images in Large Diverse DatasetsCode0
HiTSR: A Hierarchical Transformer for Reference-based Super-ResolutionCode0
High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-ResolutionCode0
An Efficient Network Design for Face Video Super-resolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified