Method

PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud (LiDAR only) [la] [PointRCNN-deprecated]


Submitted on 17 Nov. 2018 08:19 by
Shaoshuai Shi (CUHK)

Running time:0.1 s
Environment:GPU @ 2.5 Ghz (Python + C/C++)

Method Description:
This is the old version for reference.
Please see the new submission: PointRCNN
Parameters:
Please see the new submission: PointRCNN
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) 96.72 % 92.96 % 85.81 %
Car (Orientation) 96.70 % 92.74 % 85.51 %
Car (3D Detection) 86.23 % 75.81 % 68.99 %
Car (Bird's Eye View) 92.51 % 86.52 % 81.39 %
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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