Method

Fast Point R-CNN V1.1 (LiDAR only) [la] [Fast Point R-CNNv1.1]
[Anonymous Submission]

Submitted on 17 Jan. 2019 13:24 by
[Anonymous Submission]

Running time:0.06 s
Environment:GPU @ 2.5 Ghz (Python + C/C++)

Method Description:
Fixed some bug and used full dataset for training.
Parameters:
TBD
Latex Bibtex:
TBD

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) 90.59 % 89.71 % 88.13 %
Car (3D Detection) 84.28 % 75.73 % 67.39 %
Car (Bird's Eye View) 88.03 % 86.10 % 78.17 %
This table as LaTeX


2D object detection 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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