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Research map / 3D vision / Depth and stereo

Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects

CVPR 2022 · 3D vision › Depth and stereo · approach: Feed-forward 3D reconstruction · 52 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Fuse region and depth modalities (ablation)ICG · OPTAUC: 8.94 -> 16.54Helped
Add region modality (ablation)ICG · YCB-VideoADD AUC (%): 66.1 -> 86.4Helped
Add depth modality (ablation)ICG · ChoiTranslation RMS: 41.65 -> 0.04Helped
Add depth modality (ablation)ICG · YCB-VideoADD-S AUC (%): 42.8 -> 96.5Helped
Add regularization (ablation)ICG · OPTAUC: 14.48 -> 16.54Helped
Add regularization (ablation)ICG · YCB-VideoADD AUC (%): 72.0 -> 86.4Helped
Add regularization (ablation)ICG · ChoiTranslation RMS: 0.04 -> 0.04No clear effect
Add occlusion handling (ablation)ICG · YCB-VideoADD-S AUC (%): 91.9 -> 96.5Helped
Use ICG instead of SRT3D3D tracking · OPT averageAUC: 15.73 -> 16.54Helped
Use ICG instead of se(3)-TrackNetYCB-Video tracking · YCB-Video all framesADD-S AUC (%): 95.7 -> 96.5Helped
Run tracking on a single CPU core without a GPUICG · YCB-VideoSpeed (Hz): 90.9 Hz -> 788.4 HzHelped

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