Method

Multi-task Part Fusion [MPFusion]


Submitted on 9 Dec. 2022 11:24 by
sheng guang (Bit)

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
This is a fusion algorithm based on image and lidar.
The method of multi task combination can achieve
high accuracy while ensuring the speed of the fusion
algorithm
Parameters:
None
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) 96.35 % 95.53 % 92.81 %
Car (Orientation) 96.33 % 95.35 % 92.48 %
Car (3D Detection) 87.71 % 81.46 % 76.84 %
Car (Bird's Eye View) 92.40 % 89.10 % 86.28 %
Pedestrian (Detection) 74.08 % 63.86 % 60.01 %
Pedestrian (Orientation) 69.63 % 59.11 % 55.25 %
Pedestrian (3D Detection) 53.19 % 45.45 % 42.66 %
Pedestrian (Bird's Eye View) 57.82 % 48.95 % 46.31 %
Cyclist (Detection) 90.42 % 77.90 % 72.35 %
Cyclist (Orientation) 90.23 % 77.58 % 71.94 %
Cyclist (3D Detection) 83.96 % 67.17 % 60.37 %
Cyclist (Bird's Eye View) 84.50 % 69.72 % 62.92 %
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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