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Research map / Image generation / Editing and style transfer

Domain Adaptive Image-to-Image Translation

CVPR 2020 · Image generation › Editing and style transfer · approach: Image-to-image translation · 31 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Adapt the source-domain StarGAN with DAI2IStarGAN on stylized CelebA · Stylized CelebA, SmilingACC (%): 15.3 -> 96.1Helped
Adapt the source-domain StarGAN with DAI2IStarGAN on stylized CelebA · Stylized CelebA, MustacheFID: 178.9 -> 14.2Helped
Adapt StarGAN with DAI2IStarGAN on sketch expression manipulation · Sketchexpression recognition (%): 26.3 -> 68.7Helped
Adapt StarGAN with DAI2IStarGAN on painting expression manipulation · Paintingexpression recognition (%): 30.7 -> 55.1Helped
Adapt StarGAN with DAI2IStarGAN on cat-face expression manipulation · Cat facesexpression recognition (%): 22.9 -> 43.0Helped
Add adaptation loss LADA (ablation)DAI2I · Stylized CelebA, SmilingACC (%): 0.2 -> 96.1Helped
Add reconstruction loss Lrec (ablation)DAI2I · Stylized CelebA, SmilingFID: 41.9 -> 14.9Helped
Add perceptual analogy loss LPA (ablation)DAI2I · Stylized CelebA, SmilingACC (%): 15.3 -> 96.1Helped
Add domain-specific batch normalization for feature calibration (ablation)DAI2I · Stylized CelebA, SmilingFID: 41.4 -> 14.9Helped
Add AdaIN style adaptation (ablation)DAI2I · Stylized CelebA, SmilingFID: 18.5 -> 14.9Helped
Increase the analogy-loss scale α (ablation)DAI2I · Stylized CelebAvisual output qualityHurt
Add an adversarial loss on the reconstructor output in target domain B (ablation)DAI2I · Out-of-domain image translationtarget-attribute modificationHurt

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