Method

FSFNet [FSFNet]


Submitted on 30 Sep. 2022 04:49 by
jiajia lin (tongji university)

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (Python + C/C++)

Method Description:
We present a multimodal fusion network FSFNet
Parameters:
-
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) 96.36 % 92.99 % 89.99 %
Car (Orientation) 96.29 % 92.74 % 89.65 %
Car (3D Detection) 89.69 % 78.67 % 72.01 %
Car (Bird's Eye View) 94.88 % 88.35 % 83.58 %
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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