Method

Cascaded cross-modality fusion network for 3D object Dection [CCFNET]


Submitted on 11 Nov. 2020 02:39 by
zhiyu chen (NJUPT)

Running time:0.1 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
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Parameters:
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Latex Bibtex:
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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
Cyclist (Detection) 83.76 % 69.17 % 62.87 %
Cyclist (Orientation) 72.98 % 57.70 % 51.63 %
Cyclist (3D Detection) 78.05 % 60.18 % 53.42 %
Cyclist (Bird's Eye View) 81.29 % 64.65 % 57.85 %
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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