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 981–990 of 3874 papers

TitleStatusHype
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
Efficient Non-Local Contrastive Attention for Image Super-ResolutionCode1
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo SimulationCode1
Efficient Image Super-Resolution Using Pixel AttentionCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
SynFi: Automatic Synthetic Fingerprint GenerationCode1
Tarsier: Evolving Noise Injection in Super-Resolution GANsCode1
Task Transformer Network for Joint MRI Reconstruction and Super-ResolutionCode1
TDAN: Temporally Deformable Alignment Network for Video Super-ResolutionCode1
Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient ConvolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified