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Research map / Video / Video segmentation and tracking

Depth-Aware Video Frame Interpolation

CVPR 2019 · Video › Video segmentation and tracking · approach: Video frame interpolation · 577 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use depth-aware flow projection with pretrained depth jointly optimized (ablation)DAIN · UCF101PSNR: 34.91 -> 34.99Helped
use depth-aware flow projection with pretrained depth jointly optimized (ablation)DAIN · Vimeo90KPSNR: 34.47 -> 34.71Helped
initialize depth estimation from scratch instead of using pretrained depth (ablation)DAIN · UCF101PSNR: 34.91 -> 34.85Hurt
initialize depth estimation from scratch instead of using pretrained depth (ablation)DAIN · Vimeo90KPSNR: 34.47 -> 34.30Hurt
add pretrained depth initialization to flow projection (ablation)DAIN · Vimeo90KPSNR: 34.47 -> 34.52Helped
add depth maps as contextual features (ablation)DAIN · UCF101PSNR: 34.84 -> 34.90Helped
add pretrained conv1 features and depth maps as context (ablation)DAIN · UCF101PSNR: 34.84 -> 34.97Helped
use learned hierarchical features rather than pretrained conv1 features, with depth maps (ablation)DAIN · Vimeo90KPSNR: 34.49 -> 34.71Helped
add learned hierarchical contextual features and depth maps (ablation)DAIN · Middlebury OtherIE: 2.21 -> 2.04Helped
use DAIN instead of MEMC-Netvideo frame interpolation · Vimeo90KPSNR: 34.29 -> 34.71Helped

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