Method

point and voxel point cloud detection [PVNet]


Submitted on 12 Jun. 2020 15:58 by
wang dongxing (Dalian University of Technology)

Running time:0,1 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
Combining the characteristics of point and voxel
Parameters:
alpha=0.2
Latex Bibtex:

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) 94.84 % 92.12 % 89.27 %
Car (Orientation) 94.82 % 92.00 % 89.08 %
Car (3D Detection) 0.00 % 0.00 % 0.00 %
Car (Bird's Eye View) 0.00 % 0.00 % 0.00 %
Pedestrian (Detection) 60.58 % 50.50 % 48.48 %
Pedestrian (Orientation) 57.18 % 46.68 % 44.38 %
Pedestrian (3D Detection) 0.00 % 0.00 % 0.00 %
Pedestrian (Bird's Eye View) 0.00 % 0.01 % 0.01 %
Cyclist (Detection) 83.89 % 71.10 % 65.08 %
Cyclist (Orientation) 83.44 % 70.50 % 64.47 %
Cyclist (3D Detection) 0.00 % 0.00 % 0.00 %
Cyclist (Bird's Eye View) 0.00 % 0.00 % 0.00 %
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.
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



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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