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Research map / Image generation / Editing and style transfer

Thin-Plate Spline Motion Model for Image Animation

CVPR 2022 · Image generation › Editing and style transfer · approach: Texture and sketch synthesis · 217 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use TPS motion transformations instead of local affine transformations (ablation)Motion estimation · TaiChiHDAKD: 5.41 -> 4.96Helped
Add TPS transformation dropout during early training (ablation)TPS motion estimation · TaiChiHDAKD: 4.96 -> 4.66Helped
Add TPS transformation dropout during early training (ablation)TPS motion estimation · TaiChiHDAED: 0.153 -> 0.156Hurt
Add multi-resolution occlusion masks (ablation)Feature fusion and inpainting · TaiChiHDL1: 0.048 -> 0.046Helped
Add multi-resolution occlusion masks (ablation)Feature fusion and inpainting · TaiChiHDAED: 0.156 -> 0.150Helped
Add multi-resolution occlusion masks (ablation)Feature fusion and inpainting · TaiChiHDAKD: 4.66 -> 4.73Hurt
Add background consistency loss (ablation)Background motion predictor · TaiChiHDAKD: 4.73 -> 4.64Helped
Add warped-feature alignment loss (ablation)Inpainting network and motion estimation · TaiChiHDL1: 0.046 -> 0.045Helped
Use TPS motion estimation rather than local affine transformationsImage animation · TaiChiHDContinuity: 71.30%Helped
Use TPS motion estimation rather than local affine transformationsImage animation · TED-talksContinuity: 63.93%Helped
Use TPS motion estimation rather than local affine transformationsImage animation · VoxCelebContinuity: 80.95%Helped
Increase the number of TPS transformations from 2 to 8 in the reported matched-dimension experiments (ablation)Proposed motion representation · TaiChiHDAKD: 5.24 -> 4.67Helped

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