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Rolling Shutter Correction

Rolling Shutter Correction

Papers

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Showing 131–140 of 216 papers

TitleStatusHype
Cost Function Unrolling in Unsupervised Optical FlowCode0
Compiling Spiking Neural Networks to Mitigate Neuromorphic Hardware Constraints—0
FlowStep3D: Model Unrolling for Self-Supervised Scene Flow EstimationCode0
IMU-Assisted Learning of Single-View Rolling Shutter CorrectionCode1
Sampling and Recovery of Graph Signals based on Graph Neural Networks—0
Hybrid Backpropagation Parallel Reservoir Networks—0
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking—0
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response JacobiansCode1
Unrolling of Deep Graph Total Variation for Image DenoisingCode0
Training Stronger Baselines for Learning to OptimizeCode1
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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