Method

M3DNet: Minimalist 3D Detection Backbone for Efficient and Accurate 3D Object Detection [M3DNet]


Submitted on 2 Jun. 2025 16:39 by
Ram Prasad Padhy (IIITDM)

Running time:0.5 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
please refer paper
Parameters:
please refer paper
Latex Bibtex:
@inproceedings{m3dnet,
author = {Thurimerla Prasanth and Ram
Prasad Padhy and B. Sivaselvan},
title = {{M3DNet: Minimalist 3D
Detection Backbone for Efficient and Accurate 3D
Object Detection}},
booktitle = {{Proceedings of the 18th
International Conference on Agents and Artificial
Intelligence (ICAART)}},
volume = {3},
pages = {2258--2266},
year = {2026},
isbn = {978-989-758-796-2},
issn = {2184-433X},
doi = {10.5220/0014211000004052}
}

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) 95.00 % 91.87 % 88.69 %
Car (Orientation) 94.97 % 91.68 % 88.39 %
Car (3D Detection) 83.30 % 73.87 % 68.70 %
Car (Bird's Eye View) 90.27 % 86.97 % 81.95 %
Pedestrian (Detection) 62.00 % 51.10 % 48.77 %
Pedestrian (Orientation) 54.94 % 44.17 % 41.61 %
Pedestrian (3D Detection) 45.15 % 36.93 % 34.27 %
Pedestrian (Bird's Eye View) 50.30 % 41.84 % 39.49 %
Cyclist (Detection) 79.31 % 67.35 % 60.98 %
Cyclist (Orientation) 78.69 % 66.63 % 60.18 %
Cyclist (3D Detection) 70.47 % 55.64 % 49.24 %
Cyclist (Bird's Eye View) 75.48 % 61.04 % 54.48 %
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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