Method

Multi-branch Voxel Feature Extraction for 3D ObjectDetection from Point Cloud [MGACNet]


Submitted on 12 Sep. 2020 13:09 by
Yunqian He (Harbin Engineering University)

Running time:0.05 s
Environment:1 core @ 2.5 Ghz (Python + C/C++)

Method Description:
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Parameters:
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Latex Bibtex:
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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) 95.35 % 94.57 % 91.77 %
Car (Orientation) 95.33 % 94.44 % 91.55 %
Car (3D Detection) 86.20 % 79.18 % 74.58 %
Car (Bird's Eye View) 90.93 % 87.68 % 84.60 %
Pedestrian (Detection) 63.54 % 54.13 % 51.79 %
Pedestrian (Orientation) 60.32 % 50.52 % 47.92 %
Pedestrian (3D Detection) 43.55 % 37.50 % 35.33 %
Pedestrian (Bird's Eye View) 50.98 % 44.12 % 41.62 %
Cyclist (Detection) 85.45 % 73.66 % 67.10 %
Cyclist (Orientation) 85.32 % 73.43 % 66.87 %
Cyclist (3D Detection) 78.73 % 62.00 % 55.18 %
Cyclist (Bird's Eye View) 82.29 % 67.40 % 60.71 %
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.
This figure as: png eps pdf txt gnuplot



2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot



3D object detection results.
This figure as: png eps pdf txt gnuplot



Bird's eye view results.
This figure as: png eps pdf txt gnuplot




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