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Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields

CVPR 2022 · 3D vision › NeRF and radiance fields · approach: Dynamic and editable NeRF · 1,901 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Mip-NeRF 360 instead of mip-NeRFMip-NeRF 360 · Mip-NeRF 360 datasetPSNR: 24.04 -> 27.69Helped
Remove proposal loss (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 20.49Hurt
Remove distortion loss (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 24.41No clear effect
Replace distortion loss with Gaussian noise injection (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 24.00Hurt
Remove proposal MLP (ablation)Mip-NeRF 360 · bicycletraining time (hrs): 7.09 -> 18.89Hurt
Remove proposal MLP and apply reconstruction loss at all coarse scales (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 23.45Hurt
Reduce NeRF MLP width from 1024 to 256 hidden units (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 22.80Hurt
Replace integrated positional encoding with NeRF positional encoding (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 23.87Hurt
Remove contraction and use additional positional encoding frequencies (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 23.77Hurt
Replace contraction and ray spacing with DONeRF's parameterization (ablation)Mip-NeRF 360 · bicyclePSNR: 24.37 -> 23.99Hurt
Remove off-axis positional encoding features (ablation)Mip-NeRF 360 · bicycleSSIM: 0.687 -> 0.664Hurt
Remove proposal-weight annealing (ablation)Mip-NeRF 360 · bicycleSSIM: 0.687 -> 0.679Hurt

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