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CarFusion: Combining Point Tracking and Part Detection for Dynamic 3D Reconstruction of Vehicles

CVPR 2018 · 3D vision › Depth and stereo · approach: Learned optical and scene flow · 79 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Fuse structured part detections with unstructured feature tracks (ablation)CarFusion · Straightreprojection RMSE: 7.1 -> 2.5Helped
Fuse structured part detections with unstructured feature tracks (ablation)CarFusion · Turningreprojection RMSE: 5.83 -> 3.1Helped
Fuse structured part detections with unstructured feature tracks (ablation)CarFusion · Multireprojection RMSE: 4.47 -> 2.2Helped
Fine-tune the detector using reprojected 3D part locations (ablation)CarFusion · Intersection DatasetPCK (α = 0.1): 87.1 -> 91.4Helped
Fine-tune the detector using reprojected 3D part locations (ablation)CarFusion · Intersection DatasetPCK (α = 0.2): 91.8 -> 94.5Helped
Use temporal integration of structured detections without feature-track fusion (ablation)T-cRANSAC · Straightreprojection RMSE: 12.24 -> 17.8; 8.52 -> 7.1Mixed
Use temporal integration of structured detections without feature-track fusion (ablation)T-cRANSAC · Turningreprojection RMSE: 8.94 -> 12.5; 6.95 -> 5.83Mixed
Use temporal integration of structured detections without feature-track fusion (ablation)T-cRANSAC · Multireprojection RMSE: 7.45 -> 14.3; 5.3 -> 4.47Mixed
Apply multiview bootstrapping to the detector (ablation)cRANSAC · Straightreprojection RMSE: 12.24 -> 8.52Helped
Apply multiview bootstrapping to the detector (ablation)T-cRANSAC · Straightreprojection RMSE: 17.8 -> 7.1Helped
Apply multiview bootstrapping to the detector (ablation)CarFusion · Straightreprojection RMSE: 16.8 -> 2.5Helped

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