Method

forground depth guide network [FDGNet]
http://my.site.net/downloads

Submitted on 26 Feb. 2024 04:04 by
家艺 于 (江南大学)

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

Method Description:
using forground depth to guide the feature studying
Parameters:
alpha=0.2
Latex Bibtex:
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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) 96.44 % 91.31 % 83.51 %
Car (Orientation) 96.35 % 90.92 % 82.90 %
Car (3D Detection) 27.22 % 16.53 % 13.52 %
Car (Bird's Eye View) 36.25 % 23.27 % 19.56 %
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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