Method

WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection [WeakM3D]
https://github.com/SPengLiang/WeakM3D

Submitted on 5 Oct. 2021 15:56 by
Peng Liang (ZheJiang University)

Running time:0.08 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
a novel method towards weakly supervised monocular
3d object detection.
Parameters:
lr=1e-4
Latex Bibtex:
@inproceedings{peng2022weakm3d,
title={WeakM3D: Towards Weakly Supervised
Monocular 3D Object Detection},
author={Peng, Liang and Yan, Senbo and Wu, Boxi
and Yang, Zheng and He, Xiaofei and Cai, Deng},
booktitle={ICLR},
year={2022}
}

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) 94.51 % 91.81 % 85.35 %
Car (Orientation) 41.21 % 41.50 % 38.11 %
Car (3D Detection) 5.03 % 2.26 % 1.63 %
Car (Bird's Eye View) 11.82 % 5.66 % 4.08 %
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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