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 111–120 of 3874 papers

TitleStatusHype
AnySR: Realizing Image Super-Resolution as Any-Scale, Any-ResourceCode2
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
Image Restoration with Mean-Reverting Stochastic Differential EquationsCode2
Image Super-Resolution Using Very Deep Residual Channel Attention NetworksCode2
Adaptive Super Resolution For One-Shot Talking-Head GenerationCode2
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and ResultsCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Dual Aggregation Transformer for Image Super-ResolutionCode2
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture ModelsCode2
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differencesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified