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 3351–3375 of 3874 papers

TitleStatusHype
Super-Resolution for Practical Automated Plant Disease Diagnosis System—0
Super-Resolution for Remote Sensing Imagery via the Coupling of a Variational Model and Deep Learning—0
Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris—0
Super Resolution for Turbulent Flows in 2D: Stabilized Physics Informed Neural Networks—0
Vision-Informed Flow Image Super-Resolution with Quaternion Spatial Modeling and Dynamic Flow Convolution—0
Super-resolution Guided Pore Detection for Fingerprint Recognition—0
Super-Resolution Harmonic Retrieval of Non-Circular Signals—0
Super-resolution image display using diffractive decoders—0
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN—0
Super Resolution image reconstructs via total variation-based image deconvolution: a majorization-minimization approach—0
Super-resolution imaging using super-oscillatory diffractive neural networks—0
Super-resolution in disordered media using neural networks—0
A hybrid approach of interpolations and CNN to obtain super-resolution—0
Can Super Resolution be used to improve Human Pose Estimation in Low Resolution Scenarios?—0
Super-resolution in Molecular Dynamics Trajectory Reconstruction with Bi-Directional Neural Networks—0
Super-resolution meets machine learning: approximation of measures—0
Super-resolution Method for Coherent DOA Estimation of Multiple Wideband Sources—0
Superresolution method for data deconvolution by superposition of point sources—0
Super-resolution method using sparse regularization for point-spread function recovery—0
Super-resolution MRI Using Finite Rate of Innovation Curves—0
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement—0
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction—0
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified