Method

Ground Aware Monocular 3D Object Detection [Ground-Aware]
https://github.com/Owen-Liuyuxuan/visualDet3D

Submitted on 8 Apr. 2021 10:36 by
Yuxuan LIU (Hong Kong University of Science and Technology)

Running time:0.05 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Ground aware convolution and preprocessing
Parameters:
default
Latex Bibtex:
@ARTICLE{9327478,
author={Y. {Liu} and Y. {Yuan} and M. {Liu}},
journal={IEEE Robotics and Automation Letters},
title={Ground-aware Monocular 3D Object
Detection for Autonomous Driving},
year={2021},
doi={10.1109/LRA.2021.3052442}}

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) 92.33 % 82.05 % 62.08 %
Car (Orientation) 90.98 % 80.05 % 60.51 %
Car (3D Detection) 21.65 % 13.25 % 9.91 %
Car (Bird's Eye View) 29.81 % 17.98 % 13.08 %
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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