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Research map / Video / Video segmentation and tracking

FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation

CVPR 2020 · Video › Video segmentation and tracking · approach: Video frame interpolation · 79 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use structure-to-texture feature generation for frame interpolation instead of optical-flow pixel synthesisFeFlow · Vimeo90K test setPSNR: 34.71 -> 35.28Helped
Use structure-to-texture feature generation for frame interpolation instead of optical-flow pixel synthesisFeFlow · Adobe240fpsPSNR: 32.51 -> 32.66Helped
Use structure-to-texture feature generation for frame interpolation instead of optical-flow pixel synthesisFeFlow · OccPSNR: 36.98 -> 37.12Helped
Add edge-channel structure guidance and edge loss (ablation)FeFlow · Vimeo90K test setPSNR: 34.16 -> 34.84Helped
Add edge-channel structure guidance and edge loss (ablation)FeFlow · Adobe240fpsPSNR: 32.52 -> 32.54No clear effect
Add triangle alignment loss (ablation)FeFlow · Vimeo90K test setPSNR: 34.84 -> 35.28Helped
Add triangle alignment loss (ablation)FeFlow · Adobe240fpsPSNR: 32.54 -> 32.66Helped
Use 16 flow-attention groups instead of 1 (ablation)FeFlow · OccPSNR: 35.25 -> 37.12Helped
Use 16 flow-attention groups instead of 4 (ablation)FeFlow · Vimeo90K test setPSNR: 35.02 -> 35.28Helped
Use 16 flow-attention groups instead of 4 (ablation)FeFlow · Adobe240fpsPSNR: 32.54 -> 32.66Helped

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