Method

SA3DNet: An Attention-Based and Semantic-Aware MultiModal 3D DetectionNetwork [la] [st] [SA3DNet]
[Anonymous Submission]

Submitted on 7 Jan. 2022 07:51 by
[Anonymous Submission]

Running time:0.05 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
Attention-Based and Semantic-Aware
Parameters:
no
Latex Bibtex:
no

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) 96.57 % 93.62 % 88.65 %
Car (Orientation) 96.56 % 93.55 % 88.56 %
Car (3D Detection) 90.49 % 82.57 % 77.88 %
Car (Bird's Eye View) 93.11 % 89.46 % 84.60 %
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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