Method

Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion [SFD]
https://github.com/LittlePey/SFD

Submitted on 17 Nov. 2021 07:21 by
Xiaopei Wu (ZheJiang University)

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

Method Description:
TBD
Parameters:
TBD
Latex Bibtex:
@inproceedings{wu2022sparse,
title={Sparse Fuse Dense: Towards High Quality 3D
Detection with Depth Completion},
author={Wu, Xiaopei and Peng, Liang and Yang,
Honghui and Xie, Liang and Huang, Chenxi and Deng,
Chengqi and Liu, Haifeng and Cai, Deng},
booktitle={CVPR},
year={2022}
}

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) 98.97 % 96.17 % 91.13 %
Car (Orientation) 98.95 % 96.05 % 90.96 %
Car (3D Detection) 91.73 % 84.76 % 77.92 %
Car (Bird's Eye View) 95.64 % 91.85 % 86.83 %
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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