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 831–840 of 3874 papers

TitleStatusHype
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
Azimuth Super-Resolution for FMCW Radar in Autonomous DrivingCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical FidelityCode1
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth ImagesCode1
Human Guided Ground-truth Generation for Realistic Image Super-resolutionCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
Rank-One Network: An Effective Framework for Image RestorationCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modellingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified