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Self-Supervised Geometry-Aware Encoder for Style-Based 3D GAN Inversion

CVPR 2023 · 3D vision › Face and shape · approach: Face reflectance and relightable rendering · 29 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the E3DGE encoder instead of optimization-based PTI inversionStyleSDF inversion · CelebA-HQTime (s): 246 -> 0.45(T)/0.81(S)Helped
Use E3DGE instead of the strongest baselineStyleSDF inversion · Novel View SynthesisMAE: .186 ±.016 -> .147 ± .011Helped
Add local features to synthetic training (ablation)E3DGE · CelebA-HQ source-view reconstructionMAE: .245 ± .024 -> .074 ± .007Helped
Add local features to synthetic training (ablation)E3DGE · Novel View SynthesisMAE: .241 ± .011 -> .282 ± .103Hurt
Use 2D alignment rather than raw local features (ablation)E3DGE · Novel View SynthesisMAE: .282 ± .103 -> .178 ± .007Helped
Use 3D alignment rather than raw local features (ablation)E3DGE · Novel View SynthesisMAE: .282 ± .103 -> .150 ± .011Helped
Add surface geometry supervision (ablation)E3DGE global encoder · NoW Challenge validation setMedian: 2.43 -> 1.75Helped
Add around-surface geometry supervision (ablation)E3DGE global encoder · NoW Challenge validation setMedian: 1.75 -> 1.71Helped
Add code reconstruction loss (ablation)E3DGE global encoder · NoW Challenge validation setMedian: 1.71 -> 1.66Helped
Add 3D supervision to 2D inversion training (ablation)E3DGE global encoder · NoW Challenge validation setMean: 2.43 -> 2.11Helped

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