Method

Prior Distribution and Perception Radius [PR-SSD]
[Anonymous Submission]

Submitted on 22 Nov. 2023 11:43 by
[Anonymous Submission]

Running time:0.02 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
The paper will be described in detail after
acceptance
Parameters:
\alpha=0.2
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) 97.64 % 95.18 % 92.48 %
Car (Orientation) 97.62 % 95.10 % 92.33 %
Car (3D Detection) 89.69 % 81.49 % 76.71 %
Car (Bird's Eye View) 94.23 % 90.78 % 86.14 %
Pedestrian (Detection) 62.55 % 53.52 % 50.04 %
Pedestrian (Orientation) 60.89 % 51.15 % 47.65 %
Pedestrian (3D Detection) 45.08 % 38.52 % 36.23 %
Pedestrian (Bird's Eye View) 50.38 % 43.58 % 41.36 %
Cyclist (Detection) 85.78 % 75.64 % 70.35 %
Cyclist (Orientation) 85.63 % 75.28 % 69.93 %
Cyclist (3D Detection) 80.01 % 65.94 % 58.71 %
Cyclist (Bird's Eye View) 83.44 % 70.88 % 63.43 %
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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