Method

IOU-based single stage detector [WHUT-iou_ssd]
https://github.com/liangzhao123/IOU-SSD

Submitted on 27 Feb. 2021 09:56 by
liang zhao (Wuhan University of Technology )

Running time:0.045s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
we use the IOU score to select the final detection
results from box proposals, which distinguished our
method with previous methods.
Parameters:
lr=0.002,epoch=50,training on the training split
(3742 frame) and interfere on the official kitti
testing data(7518)
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) 95.77 % 94.54 % 91.91 %
Car (Orientation) 95.76 % 94.45 % 91.75 %
Car (3D Detection) 89.84 % 81.37 % 76.83 %
Car (Bird's Eye View) 94.22 % 90.31 % 85.83 %
Pedestrian (Detection) 66.60 % 58.03 % 55.82 %
Pedestrian (Orientation) 63.62 % 54.44 % 51.89 %
Pedestrian (3D Detection) 46.41 % 40.53 % 38.48 %
Pedestrian (Bird's Eye View) 50.30 % 45.24 % 43.28 %
Cyclist (Detection) 87.31 % 79.98 % 74.30 %
Cyclist (Orientation) 87.18 % 79.40 % 73.70 %
Cyclist (3D Detection) 79.38 % 65.98 % 59.56 %
Cyclist (Bird's Eye View) 82.35 % 70.53 % 63.19 %
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.
This figure as: png eps pdf txt gnuplot




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