Method

MSMA V1 [MSMA V1]
[Anonymous Submission]

Submitted on 23 Feb. 2025 05:59 by
[Anonymous Submission]

Running time:0.5 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
after publication
Parameters:
after publication
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) 95.21 % 93.98 % 90.94 %
Car (Orientation) 95.19 % 93.84 % 90.71 %
Car (3D Detection) 86.06 % 77.21 % 71.89 %
Car (Bird's Eye View) 91.35 % 87.70 % 84.38 %
Pedestrian (Detection) 62.22 % 53.10 % 50.28 %
Pedestrian (Orientation) 58.85 % 49.31 % 46.35 %
Pedestrian (3D Detection) 42.89 % 36.32 % 34.33 %
Pedestrian (Bird's Eye View) 48.10 % 41.94 % 40.05 %
Cyclist (Detection) 85.61 % 74.02 % 67.70 %
Cyclist (Orientation) 85.31 % 73.69 % 67.38 %
Cyclist (3D Detection) 75.60 % 60.30 % 53.83 %
Cyclist (Bird's Eye View) 79.61 % 65.12 % 58.84 %
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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