Method

Voxel Feature Pyramid Network [HRI-VoxelFPN]
[Anonymous Submission]

Submitted on 20 Jun. 2019 13:29 by
[Anonymous Submission]

Running time:0.02 s
Environment:GPU @ 2.5 Ghz (Python + C/C++)

Method Description:
One stage 3D detector based on VoxelNet
Multi-scale voxelized feature aggregation
Parameters:
TBA
Latex Bibtex:
Latex Bibtex:
@article{wang2019voxelFPN,
title={Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds},
author={Wang, Bei and An, Jianping and Cao,
Jiayan},
journal={arXiv preprint arXiv:1907.05286v2},
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) 90.66 % 89.89 % 80.97 %
Car (Orientation) 90.43 % 89.27 % 80.31 %
Car (3D Detection) 85.48 % 76.14 % 68.05 %
Car (Bird's Eye View) 89.20 % 87.63 % 79.23 %
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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