Method

MonoGRNet [MonoGRNet]
[Anonymous Submission]

Submitted on 16 Mar. 2019 06:16 by
[Anonymous Submission]

Running time:0.04s
Environment:NVIDIA P40

Method Description:
MonoGRNet: A Geometric Reasoning Network for
Monocular 3D Object Localization
Parameters:
Latex Bibtex:
@article{qin2019monogrnet,
title={MonoGRNet: A Geometric Reasoning Network
for 3D Object Localization},
author={Zengyi Qin and Jinglu Wang and Yan Lu},
journal={The Thirty-Third AAAI Conference on
Artificial Intelligence (AAAI-19)},
year={2019}
}

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) 87.23 % 77.46 % 61.12 %
Car (3D Detection) 11.29 % 12.90 % 11.34 %
Car (Bird's Eye View) 20.55 % 16.37 % 15.16 %
This table as LaTeX


2D object detection results.
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3D object detection results.
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Bird's eye view results.
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