Method

CoDMono: Complementary Depth Fusion for Real-Time Monocular 3D Object Detection [CoDMono]
[Anonymous Submission]

Submitted on 28 Jul. 2026 13:50 by
[Anonymous Submission]

Running time:0.02 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
new method in 3D object detection
Parameters:
kitti only train
Latex Bibtex:

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) 94.49 % 93.53 % 88.30 %
Car (Orientation) 94.37 % 93.23 % 87.73 %
Car (3D Detection) 29.19 % 19.65 % 17.71 %
Car (Bird's Eye View) 37.29 % 25.97 % 23.20 %
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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