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A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis

NeurIPS 2021 · 3D vision › Face and shape · approach: 3D shape generative modeling · 8 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace global shading by local points-specific shading (ablation)ShadeGAN · BFMFID: 17.7 -> 30.1Hurt
replace global shading by local points-specific shading (ablation)ShadeGAN · BFMSIDE: 0.607 -> 0.754Hurt
replace global shading by local points-specific shading (ablation)ShadeGAN · BFMMAD: 14.52 -> 18.18Hurt
remove dependence of albedo on lighting (ablation)ShadeGAN · BFMFID: 17.7 -> 19.2Hurt
remove dependence of albedo on lighting (ablation)ShadeGAN · BFMMAD: 14.52 -> 14.53No clear effect
remove albedo dependence on viewpoint (ablation)ShadeGAN · BFMFID: 17.7 -> 18.6Hurt
remove albedo dependence on viewpoint (ablation)ShadeGAN · BFMMAD: 14.52 -> 14.88Hurt
use manually tuned lighting prior instead of data-driven prior (ablation)ShadeGAN · BFMFID: 17.7 -> 20.2Hurt
use manually tuned lighting prior instead of data-driven prior (ablation)ShadeGAN · BFMMAD: 14.52 -> 15.38Hurt
add efficient volume rendering via surface tracking (ablation)ShadeGAN · BFMSIDE: 0.607 -> 0.673Hurt
add efficient volume rendering via surface tracking (ablation)ShadeGAN · CelebAtraining time (h): 92.3 -> 70.2Helped
add efficient volume rendering via surface tracking (ablation)ShadeGAN · CelebAinference time (s): 0.343 -> 0.179Helped

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