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 911–920 of 3874 papers

TitleStatusHype
Deep Space-Time Video Upsampling NetworksCode1
BF-STVSR: B-Splines and Fourier---Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B ImageryCode1
Large Kernel Distillation Network for Efficient Single Image Super-ResolutionCode1
SinIR: Efficient General Image Manipulation with Single Image ReconstructionCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and BeyondCode1
Accelerating the Super-Resolution Convolutional Neural NetworkCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified