Method

DVF (Voxel-RCNN) [DVF-V]


Submitted on 17 Oct. 2021 17:42 by
Anas Mahmoud (University of Toronto)

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

Method Description:
Applying Dense Voxel Fusion to Voxel-RCNN
Parameters:
TBD
Latex Bibtex:
@article{mahmoud2022dense,
title={Dense Voxel Fusion for 3D Object
Detection},
author={Mahmoud, Anas and Hu, Jordan SK and
Waslander, Steven L},
journal={WACV},
year={2023}
}

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) 96.60 % 95.77 % 90.89 %
Car (Orientation) 96.59 % 95.63 % 90.71 %
Car (3D Detection) 89.40 % 82.45 % 77.56 %
Car (Bird's Eye View) 93.12 % 89.42 % 86.50 %
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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