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Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

CVPR 2018 · Video › Video segmentation and tracking · approach: Video frame interpolation · 867 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Train to predict more intermediate frames jointly (one to seven) (ablation)Super SloMo · Adobe240-fpsPSNR: 30.26 -> 31.19Helped
Add flow interpolation refinement (ablation)Super SloMo · Adobe240-fpsPSNR: 30.34 -> 31.19Helped
Add visibility maps for occlusion reasoning (ablation)Super SloMo · Adobe240-fpsPSNR: 31.16 -> 31.19No clear effect
Add perceptual loss (ablation)Super SloMo · Adobe240-fpsPSNR: 30.96 -> 31.19Helped
Add warping loss (ablation)Super SloMo · Adobe240-fpsPSNR: 30.52 -> 31.19Helped
Add smoothness loss (ablation)Super SloMo · Adobe240-fpsPSNR: 31.19 -> 31.19No clear effect
Train on the full video dataset instead of Adobe240fps only (ablation)Super SloMo · UCF101PSNR: 32.84 -> 33.14Helped
Use Super SloMo rather than SepConvvideo interpolation · UCF101PSNR: 33.02 -> 33.14Helped
Use Super SloMo rather than FlowNet2video interpolation · slowflowIE: 5.35 -> 6.14Hurt
Use Super SloMo rather than FlowNet2video interpolation · high-frame-rate SintelPSNR: 30.79 -> 32.38Helped
Use the multi-frame interpolation setting rather than DVFunsupervised optical flow · KITTI 2012EPE: 14.6 -> 13.0Helped

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