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3D Object Detection on Waymo to nuScenes (val)

52.99APBEVBi3D
11.826822.513433.243.8866Mar 10, 2023May 18, 2023Jul 27, 2023Oct 4, 2023Dec 13, 2023Feb 20, 2024Apr 30, 2024

Evaluation results

MethodLinks
Bi3DBackbone=PV-RCNN, Annotation Budget=1%2023.0352.9949.17——————————————————
Bi3D (w/ SN)Backbone=Voxel R-CNN, Annotation Budget=1%2023.0352.73———————————————————
Bi3DDetector=SECOND-IoU, Target Sample Budget=1%2023.0342.1526.24——————————————————
Lidar DistillDetector=SECOND-IoU2023.0340.6622.86——————————————————
ST3DDetector=SECOND-IoU2023.0335.9220.19——————————————————
SNDetector=SECOND-IoU2023.0333.2318.57——————————————————
Source OnlyDetector=SECOND-IoU, Domain Adaptation=None2023.0332.9117.24——————————————————
PEREBackbone=PVRCNN2024.0420.0114.3635.219.3322.8317.6116.1822.8613.7836.398.6338.656.4735.97——————
PEREBackbone=SECOND2024.0419.5713.6934.4828.7623.7638.5315.4548.1511.4742.288.7946.455.8434.35——————
ST3DBackbone=PVRCNN2024.0418.9513.1534.796.9821.6210.4315.8920.9113.9337.656.1722.73.915.01——————
DTSBackbone=PVRCNN2024.0418.6212.5934.555.6520.644.6314.7313.1113.0330.086.5925.424.1116.72——————
LDBackbone=PVRCNN2024.0418.3712.4733.871.8420.121.5415.216.2713.4733.786.0521.923.8314.44——————
ST3D++Backbone=PVRCNN2024.0418.1512.4233.46-0.4520.574.2114.7613.3112.4124.856.2323.094.2918.19——————
ST3DBackbone=SECOND2024.0417.6411.8832.0716.7122.4931.9513.4534.458.9224.787.435.134.2217.33——————
ST3D++Backbone=SECOND2024.0417.2811.6631.815.3621.3225.8912.7829.869.3127.457.2734.074.3618.8——————
LDBackbone=SECOND2024.0416.911.4630.9511.122.0329.5712.5528.298.3420.87.1933.414.0115.13——————
Source OnlyBackbone=PVRCNN2024.0416.3310.4633.54—19.86—12.78—9.46—2.67—2.06———————
DTSBackbone=SECOND2024.0416.0311.2629.855.621.3926.2611.420.418.7123.346.8530.643.6811.65——————
Source OnlyBackbone=SECOND2024.0413.418.0728.73—16.32—8.42—5.31—3.09—2.57———————
10 f. + const LRTarget Frames=10, Learning Rate=constant2025.12——————————————————53.5744.56
10 f. + L2-SPTarget Frames=10, Regularization=L2-SP2025.12——————————————————56.1447.13
10 f. + LR fadingTarget Frames=10, Learning Rate=fading2025.12——————————————————44.0135
Bi3DNumber of frames=2812025.12——————————————————30.8111.65
CMT2025.12——————————————————26.387.22
DG-BEVBranch=DG2024.10——————————————6656.847.230.3——
Direct TransferBranch=—2024.10——————————————64.955.213.33.2——
Diverse Frame Selection AlgorithmNumber of frames=10, Learning rate strategy=constant2025.12——————————————————29.5710.41
Diverse Frame Selection AlgorithmNumber of frames=100, Learning rate strategy=constant2025.12——————————————————32.1412.98
Diverse Frame Selection AlgorithmNumber of frames=281, Learning rate strategy=constant2025.12——————————————————33.4114.25
OracleBranch=—2024.10——————————————17.8458.747.5——
OursBranch=DG2024.10——————————————65.654.747.732.6——
Ours (1%)Branch=UDGA, Target Label Ratio=1%2024.10——————————————65.654.753.440.9——
Ours (5%)Branch=UDGA, Target Label Ratio=5%2024.10——————————————65.654.757.144.8——
SEE2025.12——————————————————14.725.71
Source onlyAdaptation Protocol=Source only baseline2025.12——————————————————19.16—
Source onlyadaptation_type=Baseline2025.12——————————————————9.01—
SSDA3DNumber of frames=2812025.12——————————————————33.0113.85
ST3D2025.12——————————————————22.993.83
Stat-Norm2025.12——————————————————22.293.13
Target domainAdaptation Protocol=Target domain baseline2025.12——————————————————35.51—
Target domainadaptation_type=Oracle/Upper Bound2025.12——————————————————70.56—
TODANumber of frames=2812025.12——————————————————32.1813.02