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Dynamic Spatial Propagation Network for Depth Completion

AAAI 2022 · Architectures and efficiency › CNN design · approach: Dense matching and estimation CNNs · 126 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace fixed CSPN propagation with dynamic attention-based DySPN (ablation)7×7 CSPN · KITTI DC validationRMSE (mm): 811.0 -> 769.0Helped
Increase DySPN iterations from 6 to 12 (ablation)7×7 DySPN · KITTI DC validationRMSE (mm): 769.0 -> 768.1No clear effect
Use softmax instead of sigmoid attention (ablation)7×7 DySPN · KITTI DC validationRMSE (mm): 769.0 -> 770.0No clear effect
Add diffusion suppression (ablation)7×7 DySPN · KITTI DC validationRMSE (mm): 769.0 -> 763.9Helped
Add weight decay 5×10^5 (ablation)7×7 DySPN with DS · KITTI DC validationRMSE (mm): 763.9 -> 753.2Helped
Add weight decay 10^5 (ablation)7×7 DySPN with DS · KITTI DC validationRMSE (mm): 763.9 -> 752.9Helped
Add weight decay 5×10^6 (ablation)7×7 DySPN with DS · KITTI DC validationRMSE (mm): 763.9 -> 755.8Helped
Add stochastic depth without weight decay (ablation)7×7 DySPN with DS · KITTI DC validationRMSE (mm): 763.9 -> 745.8Helped
Use stochastic depth together with weight decay 10^5 instead of stochastic depth alone (ablation)7×7 DySPN with DS · KITTI DC validationRMSE (mm): 745.8 -> 747.0Hurt
Use dilated neighborhoods (ablation)7×7 DySPN · KITTI DC validationRMSE (mm): 757.2 -> 748.5Helped
Use deformable neighborhoods (ablation)7×7 DySPN · KITTI DC validationRMSE (mm): 757.2 -> 739.4Helped
Use dilated neighborhoods (ablation)7×7 DySPN · KITTI DC validationruntime (ms): 38 -> 6.9Helped

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