Method

BADet: Boundary-Aware 3D Object Detection from Point Clouds [BADet]
https://github.com/rui-qian/BADet

Submitted on 27 Feb. 2021 07:34 by
Rui Qian (Renmin University of China)

Running time:0.14 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
[elsevier]:
https://doi.org/10.1016/j.patcog.2022.108524

[arXiv]: https://arxiv.org/abs/2104.10330
Parameters:
TBD
Latex Bibtex:
@inproceedings{qian_2022_BADet,
title = {{BADet}: Boundary-Aware {3D} Object
Detection
from Point Clouds},
booktitle = {Pattern Recognition},
volume = {125},
pages = {108524},
year = {2022},
publisher={Elsevier},
author = {Rui Qian and Xin Lai and Xirong Li},
}

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) 98.75 % 95.61 % 90.64 %
Car (Orientation) 98.65 % 95.34 % 90.28 %
Car (3D Detection) 89.28 % 81.61 % 76.58 %
Car (Bird's Eye View) 95.23 % 91.32 % 86.48 %
This table as LaTeX

2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot



3D object detection results.
This figure as: png eps pdf txt gnuplot



Bird's eye view results.
This figure as: png eps pdf txt gnuplot




eXTReMe Tracker