Method

RangeDet (Offiical) [RangeDet (Official)]
https://github.com/tusen-ai/RangeDet

Submitted on 11 Sep. 2022 07:59 by
Wu Wu (Syracuse University)

Running time:0.02 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
RangeDet:In Defense of Range View for LiDAR-based
3D Object Detection
Parameters:
None
Latex Bibtex:
@InProceedings{Fan_2021_ICCV,
author = {Fan, Lue and Xiong, Xuan and
Wang, Feng and Wang, Naiyan and Zhang, ZhaoXiang},
title = {RangeDet: In Defense of Range
View for LiDAR-Based 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF
International Conference on Computer Vision
(ICCV)},
month = {October},
year = {2021},
}

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) 95.50 % 94.64 % 91.77 %
Car (Orientation) 95.48 % 94.51 % 91.57 %
Car (3D Detection) 85.41 % 77.36 % 72.60 %
Car (Bird's Eye View) 90.93 % 87.67 % 82.92 %
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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