Method

SH3D [SH3D]


Submitted on 17 Sep. 2024 05:53 by
Xiaoning Zhang (Xi’an Jiaotong University)

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

Method Description:
This is an algorithm for 3D object detection based
on a single image.
Parameters:
None
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) 95.79 % 87.33 % 77.76 %
Car (Orientation) 95.49 % 86.67 % 77.04 %
Car (3D Detection) 26.80 % 18.12 % 15.42 %
Car (Bird's Eye View) 35.64 % 25.25 % 22.09 %
Pedestrian (Detection) 59.74 % 45.64 % 41.29 %
Pedestrian (Orientation) 52.95 % 40.07 % 36.09 %
Pedestrian (3D Detection) 9.03 % 6.05 % 5.08 %
Pedestrian (Bird's Eye View) 10.26 % 6.75 % 5.61 %
Cyclist (Detection) 73.71 % 51.59 % 44.86 %
Cyclist (Orientation) 60.19 % 41.71 % 36.43 %
Cyclist (3D Detection) 5.29 % 3.00 % 2.56 %
Cyclist (Bird's Eye View) 6.73 % 3.60 % 3.30 %
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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