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 2231–2240 of 3874 papers

TitleStatusHype
Mathematical Foundation of Sparsity-based Multi-snapshot Spectral Estimation—0
Mathematical Theory of Computational Resolution Limit in Multi-dimensions—0
Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck—0
Matrix Neural Networks—0
Matrix Variate RBM and Its Applications—0
Maximum a Posteriori on a Submanifold: a General Image Restoration Method with GAN—0
A Convex Approach for Image Hallucination—0
MaxSR: Image Super-Resolution Using Improved MaxViT—0
CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified