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 971–980 of 3874 papers

TitleStatusHype
OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing—0
Efficient Image Super-Resolution via Symmetric Visual Attention Network—0
Real3D-Portrait: One-shot Realistic 3D Talking Portrait SynthesisCode5
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token DictionaryCode2
No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy—0
The Devil is in the Details: Boosting Guided Depth Super-Resolution via Rethinking Cross-Modal Alignment and AggregationCode1
Sparsity-based background removal for STORM super-resolution imagesCode0
City Scene Super-Resolution via Geometric Error MinimizationCode0
Deep Blind Super-Resolution for Satellite VideoCode1
Video Super-Resolution Transformer with Masked Inter&Intra-Frame AttentionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified