Method

LinkNet3D: An efficient end-to-end network for 3D object detection [LinkNet3D]


Submitted on 10 Nov. 2025 06:27 by
THURIMERLA PRASANTH (Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram)

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

Method Description:
A Lidar based 3D object detection model
Parameters:
paper
Latex Bibtex:
@article{linknet3d_prasanth,
title = {LinkNet3D: An efficient end-to-end
network for 3D object detection},
journal = {Computers and Electrical Engineering},
volume = {129},
pages = {110821},
year = {2026},
issn = {0045-7906},
doi =
{https://doi.org/10.1016/j.compeleceng.2025.110821
},
url =
{https://www.sciencedirect.com/science/article/pii
/S0045790625007645},
author = {Thurimerla Prasanth and Ram Prasad Padhy
and B. Sivaselvan and Sambit Bakshi},
}

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) 95.44 % 94.05 % 91.32 %
Car (Orientation) 95.43 % 93.95 % 91.15 %
Car (3D Detection) 87.22 % 78.54 % 74.36 %
Car (Bird's Eye View) 91.71 % 88.16 % 84.85 %
Cyclist (Detection) 88.67 % 74.82 % 68.19 %
Cyclist (Orientation) 88.38 % 74.52 % 67.89 %
Cyclist (3D Detection) 76.11 % 60.47 % 53.77 %
Cyclist (Bird's Eye View) 79.47 % 64.64 % 57.99 %
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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