Method

JPVNet [JPVNet]


Submitted on 21 Aug. 2021 08:49 by
xiao ming (whu)

Running time:0.08 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
See paper
Parameters:
See paper
Latex Bibtex:
See paper

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) 96.41 % 95.52 % 90.72 %
Car (Orientation) 96.40 % 95.38 % 90.52 %
Car (3D Detection) 88.66 % 81.73 % 76.94 %
Car (Bird's Eye View) 92.78 % 89.36 % 84.37 %
Cyclist (Detection) 87.42 % 78.73 % 72.45 %
Cyclist (Orientation) 87.26 % 78.38 % 72.04 %
Cyclist (3D Detection) 80.66 % 65.41 % 59.26 %
Cyclist (Bird's Eye View) 83.46 % 69.07 % 62.73 %
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




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