Method

High Resolution SECOND [HR-SECOND]
[Anonymous Submission]

Submitted on 15 Nov. 2019 08:04 by
[Anonymous Submission]

Running time:0.11 s
Environment:1 core @ 2.5 Ghz (Python + C/C++)

Method Description:
voxel size is set to (0.025, 0.025, 0.05); split training data
into 3:1 for train/val; the rest is exactly the same as in
https://github.com/traveller59/second.pytorch
Parameters:
trained for 150 epochs with
https://github.com/traveller59/second.pytorch/blob/master/
second/configs/all.fhd.config
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) 93.72 % 90.68 % 85.63 %
Car (Orientation) 88.32 % 81.23 % 74.89 %
Car (3D Detection) 84.78 % 75.32 % 68.70 %
Car (Bird's Eye View) 91.68 % 86.40 % 81.40 %
Pedestrian (Detection) 58.68 % 46.69 % 42.93 %
Pedestrian (Orientation) 51.12 % 40.81 % 37.48 %
Pedestrian (3D Detection) 45.31 % 35.52 % 33.14 %
Pedestrian (Bird's Eye View) 50.05 % 40.06 % 36.47 %
Cyclist (Detection) 84.21 % 72.77 % 66.25 %
Cyclist (Orientation) 82.42 % 69.60 % 62.47 %
Cyclist (3D Detection) 75.83 % 60.82 % 53.67 %
Cyclist (Bird's Eye View) 78.79 % 64.21 % 57.82 %
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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