SOTAVerified

Rolling Shutter Correction

Rolling Shutter Correction

Papers

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Showing 121–130 of 216 papers

TitleStatusHype
Unrolling the Shutter: CNN to Correct Motion Distortions—0
Using Deep Neural Networks for Estimating Loop Unrolling Factor—0
The Curse of Unrolling: Rate of Differentiating Through Optimization—0
Accelerated MRI With Deep Linear Convolutional Transform Learning—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
A Deep Primal-Dual Network for Guided Depth Super-Resolution—0
A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation—0
A Design Space Study for LISTA and Beyond—0
AETomo-Net: A Novel Deep Learning Network for Tomographic SAR Imaging Based on Multi-dimensional Features—0
A Flexible Convolutional Solver for Fast Style Transfers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DFRSC-3FramesAverage PSNR (dB)34.48—Unverified
2QRSC-5FramesAverage PSNR (dB)33.5—Unverified
3DFRSC-2FramesAverage PSNR (dB)33.39—Unverified
4JAMNet-2FramesAverage PSNR (dB)32.93—Unverified
5AdaRSC-3FramesAverage PSNR (dB)28.23—Unverified
6SUNet-2FramesAverage PSNR (dB)27.76—Unverified
7JCDAverage PSNR (dB)25.59—Unverified
8DSUNAverage PSNR (dB)25.21—Unverified