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 1641–1650 of 3874 papers

TitleStatusHype
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration—0
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid NetworkCode0
Single-Image Super-Resolution Reconstruction based on the Differences of Neighboring Pixels—0
Large-scale single-photon imaging—0
Cross-Resolution Flow Propagation for Foveated Video Super-ResolutionCode1
Learning Spatiotemporal Frequency-Transformer for Low-Quality Video Super-ResolutionCode1
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images—0
Infrared Image Super-Resolution: Systematic Review, and Future TrendsCode1
Continual Learning Approaches for Anomaly DetectionCode0
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified