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Method

MonoHPE: Monocular 3D Object Detection with Height Positional Encoding [MonoHPE]


Submitted on 14 Oct. 2025 13:10 by
tian gu (ocean university of China)

Running time:0.04 s
Environment:1 core @ 2.5 Ghz (Python)

Method Description:
We propose MonoHPE
Parameters:
Optimizer:
Latex Bibtex:
@article{zhu2026monohpe,
author = {Chenxi Zhu and Zhi Li and Zhenyu Dai
and Long Zheng and Weidong Wang},
title = {{MonoHPE}: Monocular 3D Object
Detection With Height Positional Encoding},
journal = {IEEE Transactions on Circuits and
Systems for Video Technology},
year = {2026},
doi = {10.1109/TCSVT.2026.3700175},
url =
{https://doi.org/10.1109/TCSVT.2026.3700175}
}

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) 94.25 % 93.62 % 83.79 %
Car (Orientation) 94.09 % 93.12 % 83.11 %
Car (3D Detection) 27.86 % 19.51 % 16.58 %
Car (Bird's Eye View) 36.51 % 25.27 % 22.77 %
Pedestrian (Detection) 81.40 % 64.32 % 59.24 %
Pedestrian (Orientation) 72.24 % 56.35 % 51.52 %
Pedestrian (3D Detection) 16.26 % 10.62 % 9.02 %
Pedestrian (Bird's Eye View) 17.57 % 11.70 % 10.12 %
Cyclist (Detection) 71.25 % 53.33 % 46.66 %
Cyclist (Orientation) 56.11 % 41.50 % 36.81 %
Cyclist (3D Detection) 6.26 % 4.24 % 3.98 %
Cyclist (Bird's Eye View) 7.58 % 4.82 % 4.78 %
This table as LaTeX


2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
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