Method

DSGN++ [st] [DSGN++]
https://github.com/chenyilun95/DSGN2

Submitted on 20 Nov. 2021 11:57 by
Yilun Chen (CUHK)

Running time:0.2 s
Environment:GeForce RTX 2080Ti

Method Description:
TBD
Parameters:
TBD
Latex Bibtex:
@ARTICLE{chen2022dsgn++,
title={DSGN++: Exploiting Visual-Spatial Relation
for Stereo-Based 3D Detectors},
author={Chen, Yilun and Huang, Shijia and Liu, Shu
and Yu, Bei and Jia, Jiaya},
journal={IEEE Transactions on Pattern Analysis and
Machine Intelligence},
year={2022}
}

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) 98.08 % 95.70 % 88.27 %
Car (Orientation) 98.04 % 95.58 % 88.09 %
Car (3D Detection) 83.21 % 67.37 % 59.91 %
Car (Bird's Eye View) 88.55 % 78.94 % 69.74 %
Pedestrian (Detection) 69.70 % 58.09 % 54.45 %
Pedestrian (Orientation) 54.16 % 43.35 % 40.10 %
Pedestrian (3D Detection) 43.05 % 32.74 % 29.54 %
Pedestrian (Bird's Eye View) 50.26 % 38.92 % 35.12 %
Cyclist (Detection) 77.71 % 62.10 % 55.78 %
Cyclist (Orientation) 57.93 % 45.94 % 41.93 %
Cyclist (3D Detection) 62.82 % 43.90 % 39.21 %
Cyclist (Bird's Eye View) 68.29 % 49.37 % 43.79 %
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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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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