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 1526–1550 of 3874 papers

TitleStatusHype
Data-Driven Design for Fourier Ptychographic Microscopy—0
FlashSR: One-step Versatile Audio Super-resolution via Diffusion Distillation—0
HSR-Diff: Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image Compression—0
Cross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics—0
A Generalized Tensor Formulation for Hyperspectral Image Super-Resolution Under General Spatial Blurring—0
Generative Adversarial Classifier for Handwriting Characters Super-Resolution—0
Cross-Guided Optimization of Radiance Fields With Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis—0
DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images—0
First order algorithms in variational image processing—0
Astronomical Image Colorization and upscaling with Generative Adversarial Networks—0
FireSRnet: Geoscience-Driven Super-Resolution of Future Fire Risk from Climate Change—0
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models—0
Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck—0
Fingerprints of Super Resolution Networks—0
Fingerprinting Deep Image Restoration Models—0
Generative AI in Vision: A Survey on Models, Metrics and Applications—0
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery—0
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution—0
A Generative Model for Generic Light Field Reconstruction—0
Generative Powers of Ten—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
Generator From Edges: Reconstruction of Facial Images—0
Generic 3D Convolutional Fusion for image restoration—0
2D Neural Fields with Learned Discontinuities—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified