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MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling With Informative-Preserved Reconstruction and Self-Distilled Consistency

CVPR 2023 · 3D vision › 3D generation · approach: Learning 3D reconstruction from images · 5 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
pre-train with MM-3DScene instead of training from scratchVoteNet · ScanNetv2mAP@0.5: 35.4 -> 41.5Helped
pre-train with MM-3DScene instead of training from scratchVoteNet · SUN RGB-DmAP@0.5: 32.9 -> 37.3Helped
pre-train with MM-3DScene instead of training from scratchPoint Transformer · ScanNetv2mIoU: 70.6 -> 72.8Helped
pre-train with MM-3DScene instead of training from scratchPoint Transformer · S3DIS Area-5mIoU: 70.4 -> 71.9Helped
add informative-preserved masked modeling to consistency self-distillation (ablation)MM-3DScene · S3DIS Area-5mIoU: 70.9 -> 71.9Helped
add consistency self-distillation to informative-preserved masked modeling (ablation)MM-3DScene · S3DIS Area-5mIoU: 71.1 -> 71.9Helped
add progressive reconstruction to random masking (ablation)PointMAE* · S3DIS Area-5mIoU: 70.4 -> 70.6Helped
preserve informative points rather than mask them (ablation)MM-3DScene masked modeling · S3DIS Area-5mIoU: 70.2 -> 70.9Helped
add progressive reconstruction to informative-preserved masking (ablation)MM-3DScene (MM only) · S3DIS Area-5mIoU: 70.9 -> 71.1Helped
use coordinate and RGB local differences rather than coordinate differences only (ablation)MM-3DScene (MM only) · S3DIS Area-5mIoU: 70.6 -> 71.1Helped
use coordinate and RGB local differences rather than RGB differences only (ablation)MM-3DScene (MM only) · S3DIS Area-5mIoU: 70.9 -> 71.1Helped
increase the reconstruction gap beyond 0.1 (ablation)MM-3DScene (MM only) · S3DISmIoUHurt

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