Method

Multi-Task Multi-Sensor Fusion [la] [UberATG-MMF]


Submitted on 14 Nov. 2018 00:03 by
Ming Liang (Uber ATG)

Running time:0.08 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
https://eng.uber.com/research/multi-task-multi-
sensor-fusion-for-3d-object-detection/
Parameters:
See the paper.
Latex Bibtex:
@inproceedings{Liang2019CVPR,
title = {Multi-Task Multi-Sensor Fusion for 3D
Object Detection},
author = {Ming Liang* and Bin Yang* and Yun Chen
and
Rui Hu and Raquel Urtasun},
booktitle = {CVPR},
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) 97.41 % 94.25 % 89.87 %
Car (3D Detection) 88.40 % 77.43 % 70.22 %
Car (Bird's Eye View) 93.67 % 88.21 % 81.99 %
This table as LaTeX

2D object detection results.
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3D object detection results.
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Bird's eye view results.
This figure as: png eps pdf txt gnuplot




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