Method

HDNET - LIDAR only [la] [UberATG-HDNET]


Submitted on 19 Sep. 2018 21:58 by
Bin Yang (University of Toronto)

Running time:0.05 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
LIDAR+Map based detector trained on KITTI,
with map information also predicted online from single
LIDAR sweep.
Parameters:
See the paper.
Latex Bibtex:
@inproceedings{Yang2018CoRL,
title = {HDNET: Exploiting HD Maps for
3D Object Detection},
author = {Bin Yang and Ming Liang and Raquel Urtasun},
booktitle = {2nd Conference on Robot Learning (CoRL)},
year = {2018}}

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) 93.13 % 87.98 % 81.23 %
This table as LaTeX

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




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