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Research map / Image generation / Editing and style transfer

FReeNet: Multi-Identity Face Reenactment

CVPR 2020 · Image generation › Editing and style transfer · approach: Identity-preserving face manipulation · 105 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace Pix2Pix with the GAG generatorFace reenactment on RaFD · RaFDSSIM: 0.629 -> 0.659Helped
Replace Pix2Pix with the GAG generatorFace reenactment on RaFD · RaFDFID: 12.84 -> 11.67Helped
Add ULC to GAG (ablation)FReeNet · RaFDSSIM: 0.659 -> 0.711Helped
Add ULC to GAG (ablation)FReeNet · RaFDFID: 11.67 -> 13.26Hurt
Add triplet perceptual loss to GAG+ULC (ablation)FReeNet · RaFDSSIM: 0.711 -> 0.717Helped
Add triplet perceptual loss to GAG+ULC (ablation)FReeNet · RaFDFID: 13.26 -> 12.17Helped
Add cycle-consistent loss to ULC training (ablation)ULC · RaFDACE: 7.236±0.015 -> 4.526±0.015Helped
Add discriminator losses to ULC training (ablation)ULC · RaFDACE: 4.526±0.015 -> 0.895±0.010Helped
Use full FReeNet instead of Pix2PixFace reenactment · RaFDAMT: 41.3% -> 74.9%Helped
Use one unified FReeNet model for multiple identitiesMulti-identity reenactment · All transformations among n personsParameters (M), transfer: 4.5Helped
Use one unified FReeNet model for multiple identitiesMulti-identity reenactment · All transformations among n personsSpeed (FPS): 57 FPS; Pix2Pix 75, Xu et al. 73, ReenactGAN 48, X2Face 16Mixed

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