Method

PVRCNN_8369 [PVRCNN_8369]
[Anonymous Submission]

Submitted on 11 Oct. 2022 08:08 by
[Anonymous Submission]

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

Method Description:
pvrcnn based
Parameters:
a=0.1
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) 95.84 % 94.24 % 91.80 %
Car (Orientation) 95.81 % 94.08 % 91.54 %
Car (3D Detection) 87.45 % 80.25 % 76.19 %
Car (Bird's Eye View) 91.91 % 88.13 % 85.40 %
Pedestrian (Detection) 68.43 % 58.70 % 56.24 %
Pedestrian (Orientation) 63.38 % 53.36 % 50.44 %
Pedestrian (3D Detection) 47.30 % 39.41 % 36.96 %
Pedestrian (Bird's Eye View) 52.41 % 44.83 % 42.57 %
Cyclist (Detection) 85.41 % 73.68 % 66.98 %
Cyclist (Orientation) 85.19 % 73.21 % 66.48 %
Cyclist (3D Detection) 77.33 % 61.99 % 55.51 %
Cyclist (Bird's Eye View) 79.60 % 64.56 % 57.94 %
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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