Method

3D FCN [la] [3D FCN]


Submitted on 24 Jul. 2017 13:14 by
David Stutz (Max Planck Institute for Intelligent Systems)

Running time:>5 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
3DCNN

Originally submitted anonymously.
Parameters:
0-6000
Latex Bibtex:
@inproceedings{li2017iros,
title = {3D Fully Convolutional Network for Vehicle
Detection
in Point Cloud},
author = {Bo Li},
booktitle = {IROS},
year = {2017}
}

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 (Bird's Eye View) 69.94 % 62.54 % 55.94 %
This table as LaTeX


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




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