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Geometry-Constrained Car Recognition Using a 3D Perspective Network

AAAI 2020 · 3D vision › Face and shape · approach: Primitive-based shape abstraction · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace attention-based feature (RoI Align) with 3D perspective feature (ablation)Ours-det · BoxCars Mediumtop-1 accuracy: 73.97 -> 78.45Helped
replace attention-based feature with 3D perspective feature (ablation)Ours-det · BoxCars Hardtop-1 accuracy: 73.65 -> 75.18Helped
replace ABF with 3DPF (ablation)Ours-det · BoxCars Hardtop-5 accuracy: 91.13 -> 91.53No clear effect
add VP regularization loss (ablation)Ours-det · BoxCars Mediumtop-1 accuracy: 78.32 -> 78.45No clear effect
add VP regularization loss (ablation)Ours-det · BoxCars Hardtop-5 accuracy: 89.94 -> 91.53Helped
add VP regularization loss (ablation)Ours-cls · BoxCars Mediumtop-5 accuracy: 92.88 -> 93.82Helped
add VP regularization loss (ablation)Ours-cls · BoxCars Hardtop-5 accuracy: 90.50 -> 91.97Helped
add VP regularization loss (ablation)Ours-cls · BoxCars Hardtop-1 accuracy: 76.84 -> 77.08No clear effect
add VP loss, 3D box PCK at 15 epochs (ablation)Ours-det · BoxCars HardPCK: 86.70 -> 87.15Helped
add VP loss, cuboid quality at 15 epochs (ablation)Ours-det · BoxCars HardCQ: 1.69 -> 2.12Helped
add VP loss, cuboid quality at 5 epochs (ablation)Ours-det · BoxCars HardCQ: 1.48 -> 1.48No clear effect
add 3D perspective features to 2D detectorOurs-det vs Faster-RCNN · BoxCars Hardtop-1 accuracy: 62.73 -> 75.18Helped

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