Method

[la] LidarNet [LidarNet]
[Anonymous Submission]

Submitted on 2 Aug. 2017 07:09 by
[Anonymous Submission]

Running time:0.007 s
Environment:GPU @ 2.5 Ghz (C/C++)

Method Description:
Front view map from Velodyne scan
Parameters:
learning rate is 1e-4
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) 1.98 % 2.66 % 2.18 %
Car (Orientation) 0.70 % 1.09 % 0.88 %
Car (3D Detection) 0.01 % 0.02 % 0.03 %
Car (Bird's Eye View) 0.06 % 0.14 % 0.17 %
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.
This figure as: png eps pdf txt gnuplot




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