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Research map / 3D vision / NeRF and radiance fields

Removing Objects From Neural Radiance Fields

CVPR 2023 · 3D vision › NeRF and radiance fields · approach: Dynamic and editable NeRF · 59 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use confidence-based view selection instead of using all inpainted views (ablation)NeRF object removal · Synthetic objectsPSNR: 27.568 -> 29.437Helped
use confidence-based view selection instead of regular 10-frame sampling (ablation)NeRF object removal · Synthetic objectsPSNR: 27.098 -> 29.437Helped
use confidence-based view selection instead of regular 50-frame sampling (ablation)NeRF object removal · Synthetic objectsPSNR: 26.718 -> 29.437Helped
use confidence-based view selection instead of a single middle frame (ablation)NeRF object removal · Synthetic objectsPSNR: 26.232 -> 29.437Helped
use 2D inpainted RGB images with confidence-based selection instead of ignoring masked regions (ablation)NeRF object removal · Synthetic objects - MaskedPSNR: 26.126 -> 29.437Helped
add confidence-based selection to training on inpainted RGB and depth (ablation)NeRF object removal · Synthetic objects - MaskedPSNR: 27.568 -> 29.437Helped
use predicted depth instead of sensor depth (ablation)Ours · Synthetic objects - MaskedPSNR: 29.437 -> 26.540Hurt
use predicted depth instead of sensor depth (ablation)Ours · Real objects - MaskedPSNR: 25.271 -> 25.010Hurt
use confidence-based view selection rather than all inpainted views (ablation)NeRF object removal · Synthetic objectsLPIPS: 0.094 -> 0.078Helped

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