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 521–530 of 3874 papers

TitleStatusHype
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
Zero-Shot Dual-Lens Super-ResolutionCode1
Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-ResolutionCode1
Cross-Resolution Flow Propagation for Foveated Video Super-ResolutionCode1
Infrared Image Super-Resolution: Systematic Review, and Future TrendsCode1
Meta-Learned Kernel For Blind Super-Resolution Kernel EstimationCode1
Mitigating Artifacts in Real-World Video Super-Resolution ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified