Method

Consistency of Implicit and Explicit Features Matters for Monocular 3D Object Detection [CIE + DM3D]


Submitted on 16 Jun. 2022 08:22 by
anonymity anonymity (anonymity)

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
A monocular 3D object deteciton method.
Parameters:
TBA
Latex Bibtex:
@article{ye2022consistency,
title={Consistency of Implicit and Explicit
Features Matters for Monocular 3D Object
Detection},
author={Ananimities},
journal={arXiv preprint arXiv:2207.07933},
year={2022}
}

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) 79.36 % 61.54 % 53.56 %
Car (Orientation) 79.31 % 61.42 % 53.35 %
Car (3D Detection) 35.96 % 25.02 % 21.47 %
Car (Bird's Eye View) 46.17 % 33.13 % 28.80 %
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