Method

Point-Image SECOND [PI-SECOND]
[Anonymous Submission]

Submitted on 17 Feb. 2024 08:33 by
[Anonymous Submission]

Running time:0.05 s
Environment:GPU @ >3.5 Ghz (Python + C/C++)

Method Description:
20240122
Parameters:
TBD
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) 95.31 % 89.99 % 86.86 %
Car (Orientation) 95.06 % 89.29 % 85.82 %
Car (3D Detection) 81.62 % 71.46 % 66.26 %
Car (Bird's Eye View) 90.15 % 84.83 % 79.86 %
Pedestrian (Detection) 63.28 % 52.97 % 49.07 %
Pedestrian (Orientation) 57.38 % 48.05 % 44.39 %
Pedestrian (3D Detection) 50.39 % 39.98 % 35.98 %
Pedestrian (Bird's Eye View) 54.33 % 44.64 % 40.68 %
Cyclist (Detection) 87.02 % 73.44 % 67.23 %
Cyclist (Orientation) 86.80 % 72.97 % 66.52 %
Cyclist (3D Detection) 77.31 % 61.06 % 55.07 %
Cyclist (Bird's Eye View) 81.99 % 65.62 % 59.19 %
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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