Method

MMDetection3D PartA2 [mm3d_PartA2]


Submitted on 25 Feb. 2024 10:14 by
Xu Sheep (University of Science and Technology of China)

Running time:0.1 s
Environment:GPU @ >3.5 Ghz (Python)

Method Description:
Part-A^2 reproduced based on mmdetection3d v1.4.0.
all of the parameters setup are default on a single V100.
Parameters:
default
Latex Bibtex:
none

Detailed Results

Object detection and orientation estimation results. Results for object detection are given in terms of average precision (AP) and results for joint object detection and orientation estimation are provided in terms of average orientation similarity (AOS).


Benchmark Easy Moderate Hard
Car (Detection) 95.27 % 91.88 % 89.21 %
Car (Orientation) 95.05 % 91.28 % 88.48 %
Car (3D Detection) 86.82 % 76.09 % 72.74 %
Car (Bird's Eye View) 91.75 % 87.51 % 83.01 %
Pedestrian (Detection) 60.60 % 51.40 % 48.39 %
Pedestrian (Orientation) 54.51 % 45.39 % 42.50 %
Pedestrian (3D Detection) 44.67 % 36.84 % 34.48 %
Pedestrian (Bird's Eye View) 48.45 % 41.24 % 38.92 %
Cyclist (Detection) 89.05 % 78.02 % 71.63 %
Cyclist (Orientation) 88.70 % 77.15 % 70.69 %
Cyclist (3D Detection) 76.92 % 61.83 % 55.51 %
Cyclist (Bird's Eye View) 82.10 % 67.12 % 60.42 %
This table as LaTeX


2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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