Method

PatchNet [PatchNet]
https://github.com/xinzhuma/patchnet

Submitted on 5 Mar. 2020 22:51 by
yingjie cai (BUAA)

Running time:0.4 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
TBA
Parameters:
TBA
Latex Bibtex:
@InProceedings{Ma_2020_ECCV,
author = {Ma, Xinzhu and Liu, Shinan and Xia, Zhiyi
and Zhang, Hongwen and Zeng, Xingyu and Ouyang,
Wanli},
title = {Rethinking Pseudo-LiDAR Representation},
booktitle = {Proceedings of the European Conference
on Computer Vision (ECCV)},
year = {2020}
}

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) 93.82 % 90.87 % 79.62 %
Car (3D Detection) 15.68 % 11.12 % 10.17 %
Car (Bird's Eye View) 22.97 % 16.86 % 14.97 %
This table as LaTeX

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



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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