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 3841–3850 of 3874 papers

TitleStatusHype
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System—0
HAAT: Hybrid Attention Aggregation Transformer for Image Super-Resolution—0
Handheld Burst Super-Resolution Meets Multi-Exposure Satellite Imagery—0
Handling Motion Blur in Multi-Frame Super-Resolution—0
Dual Circle Contrastive Learning-Based Blind Image Super-Resolution—0
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation—0
Harnessing Artificial Intelligence To Reduce Phototoxicity in Live Imaging—0
The End Restraint Method for Mechanically Perturbing Nucleic Acids in silico—0
Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution—0
HartleyMHA: Self-Attention in Frequency Domain for Resolution-Robust and Parameter-Efficient 3D Image Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified