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Research map / 3D vision / NeRF and radiance fields

Learning 3D-Aware Image Synthesis With Unknown Pose Distribution

CVPR 2023 · 3D vision › NeRF and radiance fields · approach: 3D-aware generative radiance fields · 11 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use PoF3D without pose priors instead of CAMPARI3D-aware image synthesis · FFHQ, Cats, Shapenet CarsFID: 58.59 -> 4.99 (FFHQ); 37.40 -> 5.46 (Cats); 68.91 -> 3.78 (Shapenet Cars)Helped
Add symmetry loss (ablation)PoF3D · FFHQDepth Error: 0.41 -> 0.29Helped
Add a pose-aware discriminator (ablation)PoF3D · FFHQDepth Error: 1.30 -> 0.29Helped
Condition discriminator classification on predicted pose (ablation)PoF3D · FFHQDepth Error: 1.48 -> 0.29Helped
Increase pose learner learning rate to 2.5e-4 (ablation)PoF3D · FFHQFID: 4.99 -> 122.07Hurt
Decrease pose learner learning rate to 2.5e-6 (ablation)PoF3D · FFHQFID: 4.99 -> 10.20Hurt
Use pose-free generation with a learned pose from the latent codePoF3D · Shapenet CarsFID: 9.68* -> 3.78Helped

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