Method

[la]SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud [SE-SSD]
https://github.com/Vegeta2020/SE-SSD

Submitted on 14 Nov. 2020 13:32 by
Weiliang Tang (CUHK)

Running time:0.03 s
Environment:1 core @ 2.5 Ghz (Python + C/C++)

Method Description:
TBA
Parameters:
TBA
Latex Bibtex:
@inproceedings{zheng2020ciassd,
title={SE-SSD: Self-Ensembling Single-Stage Object
Detector From Point Cloud},
author={Zheng, Wu and Tang, Weiliang and Jiang, Li
and Fu, Chi-Wing},
booktitle={CVPR},
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) 96.69 % 95.60 % 90.53 %
Car (Orientation) 96.55 % 95.17 % 90.00 %
Car (3D Detection) 91.49 % 82.54 % 77.15 %
Car (Bird's Eye View) 95.68 % 91.84 % 86.72 %
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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