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Frame-Consistent Recurrent Video Deraining With Dual-Level Flow

CVPR 2019 · Video › Video segmentation and tracking · approach: Learned optical flow estimation · 125 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use the proposed two-stage recurrent deraining methodvideo deraining · RainSynLight25PSNR: 32.96 -> 35.80Helped
use the proposed two-stage recurrent deraining methodvideo deraining · RainSynHeavy25PSNR: 24.13 -> 27.72Helped
use the proposed two-stage recurrent deraining methodvideo deraining · NTURainPSNR: 32.61 -> 36.05Helped
use the proposed method instead of J4RNet-Pvideo deraining · RainSynAll100SSIM: 0.7746 -> 0.8989Helped
add SF-DerainNet (ablation)the recurrent video deraining network · RainSynAll100PSNR: 21.70 -> 25.89Helped
add LSTM memory across frames (ablation)the recurrent video deraining network · RainSynAll100PSNR: 26.11 -> 25.89Helped
add the inverse recovery module (ablation)the recurrent video deraining network · RainSynAll100SSIM: 0.8683 -> 0.9043Helped
add MF-Alignment (ablation)the recurrent video deraining network · RainSynAll100SSIM: 0.9125 -> 0.9125No clear effect
add dual-level flow constraints (ablation)the proposed video deraining network · RainSynAll100temporal consistencyHelped

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