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 1271–1280 of 3874 papers

TitleStatusHype
End-to-end pipeline for simultaneous temperature estimation and super resolution of low-cost uncooled infrared camera frames for precision agriculture applications—0
Accelerated Gradient-based Design Optimization Via Differentiable Physics-Informed Neural Operator: A Composites Autoclave Processing Case Study—0
VoLUT: Efficient Volumetric streaming enhanced by LUT-based super-resolution—0
Super Resolution image reconstructs via total variation-based image deconvolution: a majorization-minimization approach—0
Do Deepfake Detectors Work in Reality?—0
Data-driven Super-Resolution of Flood Inundation Maps using Synthetic SimulationsCode0
Rapid Whole Brain Motion-robust Mesoscale In-vivo MR Imaging using Multi-scale Implicit Neural Representation—0
Deep EEG Super-Resolution: Upsampling EEG Spatial Resolution with Generative Adversarial Networks—0
Quaternion-Hadamard Network: A Novel Defense Against Adversarial Attacks with a New Dataset—0
Image Super-Resolution with Guarantees via Conformalized Generative Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified