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 461–470 of 3874 papers

TitleStatusHype
Bilateral Event Mining and Complementary for Event Stream Super-ResolutionCode1
Global Learnable Attention for Single Image Super-ResolutionCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
Guided Depth Map Super-resolution: A SurveyCode1
Deep Image PriorCode1
Hard Exudate Segmentation Supplemented by Super-Resolution with Multi-scale Attention Fusion ModuleCode1
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified