Method

Realtime 3D Object Detection for Automated Driving Using Stereo Vision and Semantic Information [st] [RT3DStereo]


Submitted on 17 Apr. 2019 18:01 by
Hendrik Königshof (KIT)

Running time:0.08 s
Environment:GPU @ 2.5 Ghz (C/C++)

Method Description:
RT3DStereo
Parameters:
RT3DStereo
Latex Bibtex:
@inproceedings{Koenigshof2019Objects,
title={{Realtime 3D Object Detection for Automated Driving Using Stereo Vision and Semantic Information}},
author={Hendrik Königshof and Niels Ole Salscheider and Christoph Stiller},
month = {Oct},
year={2019},
address = {Auckland, NZ},
Booktitle={Proc. IEEE Intl. Conf. Intelligent Transportation Systems},
url={http://www.mrt.kit.edu/z/publ/download/2019/Koenigshof2019Objects.pdf}
}

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) 56.53 % 45.81 % 37.63 %
Car (Orientation) 25.58 % 21.41 % 17.52 %
Car (3D Detection) 29.90 % 23.28 % 18.96 %
Car (Bird's Eye View) 58.81 % 46.82 % 38.38 %
Pedestrian (Detection) 41.12 % 29.30 % 25.25 %
Pedestrian (Orientation) 21.41 % 15.34 % 13.23 %
Pedestrian (3D Detection) 3.28 % 2.45 % 2.35 %
Pedestrian (Bird's Eye View) 4.72 % 3.65 % 3.00 %
Cyclist (Detection) 19.58 % 12.96 % 11.47 %
Cyclist (Orientation) 5.46 % 3.88 % 3.54 %
Cyclist (3D Detection) 5.29 % 3.37 % 2.57 %
Cyclist (Bird's Eye View) 7.03 % 4.10 % 3.88 %
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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