Method

SGFNet：Similarity-guided fusion network for 3D object detection [SGFNet]
[Anonymous Submission]

Submitted on 20 May. 2023 02:54 by
[Anonymous Submission]

Running time:0.09 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
It utilizes cross-modal attention and similarity
loss to learn the similarity between multi-modal
feature.
Parameters:
weight of similarity: 0.5
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) 98.46 % 95.60 % 92.74 %
Car (Orientation) 98.42 % 95.43 % 92.46 %
Car (3D Detection) 88.80 % 81.39 % 76.47 %
Car (Bird's Eye View) 94.01 % 90.91 % 86.12 %
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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