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Multi-View Harmonized Bilinear Network for 3D Object Recognition

CVPR 2018 · Detection and segmentation › 3D detection and driving · approach: Multi-camera BEV detection · 334 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add learned singular-value harmonization instead of fixed square-root normalizationBilinear pooling for 3D object recognition · ModelNet40average instance accuracy: 93.23 -> 94.12Helped
Add learned singular-value harmonization instead of fixed square-root normalizationBilinear pooling for 3D object recognition · ModelNet10average instance accuracy: 93.17 -> 94.93Helped
Add early sqrt and late sqrt sub-layers (ablation)MHBN · ModelNet40average instance accuracy: 93.24 -> 94.12Helped
Add late sqrt sub-layer (ablation)MHBN · ModelNet40average instance accuracy: 93.24 -> 93.63Helped
Add early sqrt and late sqrt sub-layers (ablation)MHBN · ModelNet10average instance accuracy: 93.39 -> 94.93Helped
Add early sqrt and late sqrt sub-layers (ablation)MHBN · ModelNet40average class accuracy: 90.00 -> 92.23Helped
Use 12 views instead of 6 (ablation)MHBN · ModelNet40average instance accuracy: 94.12 -> 93.42Hurt
Use 3 views instead of 6 (ablation)MHBN · ModelNet40average instance accuracy: 94.12 -> 93.78Hurt
Add depth-view features to RGB-view featuresMHBN · ModelNet40average instance accuracy: 94.1 -> 94.7Helped
Add depth-view features to RGB-view featuresMHBN · ModelNet10average instance accuracy: 94.9 -> 95.0No clear effect
Increase local feature dimension above 64 (ablation)MHBN · ModelNet10accuracyHurt
Increase local feature dimension (ablation)MHBN · ModelNet40accuracyHelped

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