Method

Sequential Point Clustering [la] [SPC]
[Anonymous Submission]

Submitted on 20 Sep. 2017 13:34 by
[Anonymous Submission]

Running time:0.4 s
Environment:4 cores @ 2.5 Ghz (Python)

Method Description:
Sequential clustering and classification of 3D points.
Parameters:
TBD
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) 25.30 % 18.83 % 17.29 %
Car (Orientation) 15.61 % 12.12 % 11.23 %
Car (3D Detection) 0.68 % 0.52 % 0.60 %
Car (Bird's Eye View) 7.28 % 5.07 % 4.19 %
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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