Method

OcTr: Octree-based Transformer for 3D Object Detection [OcTr]


Submitted on 11 Nov. 2022 11:38 by
feng yongchao (beihang university)

Running time:0.06 s
Environment:GPU @ 2.5 Ghz (Python + C/C++)

Method Description:
TBD
Parameters:
TBD
Latex Bibtex:
@inproceedings{zhou2023octr,
title={OcTr: Octree-based Transformer for 3D Object
Detection},
author={Zhou, Chao and Zhang, Yanan and Chen, Jiaxin
and Huang, Di},
booktitle={CVPR},
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) 96.48 % 95.84 % 90.99 %
Car (Orientation) 96.44 % 95.69 % 90.78 %
Car (3D Detection) 90.88 % 82.64 % 77.77 %
Car (Bird's Eye View) 93.08 % 89.56 % 86.74 %
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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