Method

3D object detection with guidance and surface feature [GS3D]


Submitted on 27 Mar. 2019 04:35 by
li buyu (cuhk)

Running time:2 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
The implementation of CVPR2019 paper GS3D: An
Efficient 3D Object Detection Framework for
Autonomous Driving.
Parameters:
N/A
Latex Bibtex:
@inproceedings{li2019gs3d,
title={GS3D: An Efficient 3D Object Detection
Framework for Autonomous Driving},
author={Li, Buyu and Ouyang, Wanli and Sheng, Lu
and Zeng, Xingyu and Wang, Xiaogang},
year={2019},
booktitle={IEEE Conference on Computer Vision and
Pattern Recognition (CVPR)}
}

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) 86.23 % 76.35 % 62.67 %
Car (Orientation) 85.79 % 75.63 % 61.85 %
Car (3D Detection) 4.47 % 2.90 % 2.47 %
Car (Bird's Eye View) 8.41 % 6.08 % 4.94 %
This table as LaTeX


2D object detection results.
This figure as: png eps pdf txt gnuplot



Orientation estimation results.
This figure as: png eps pdf txt gnuplot



3D object detection results.
This figure as: png eps pdf txt gnuplot



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




eXTReMe Tracker