Method

DCGNN: A Single-Stage 3D Object Detection Network based on Density Clustering and Graph Neural Netwo [DCGNN]
[Anonymous Submission]

Submitted on 18 Jul. 2022 17:28 by
[Anonymous Submission]

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

Method Description:
TBD
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) 96.39 % 95.36 % 90.37 %
Car (3D Detection) 89.65 % 79.80 % 74.52 %
Car (Bird's Eye View) 94.57 % 89.36 % 84.13 %
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2D object detection results.
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3D object detection results.
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Bird's eye view results.
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