Method

MMLAB LIGA-Stereo [st] [MMLAB LIGA-Stereo]
https://github.com/xy-guo/LIGA-Stereo

Submitted on 14 Jul. 2021 08:44 by
Xiaoyang Guo (The Chinese University of Hong Kong)

Running time:0.4 s
Environment:1 core @ 2.5 Ghz (Python + C/C++)

Method Description:
The final model of LIGA stereo dector
Parameters:
train with 3D & BEV LiDAR imitation
Latex Bibtex:
@InProceedings{Guo_2021_ICCV,
author = {Guo, Xiaoyang and Shi, Shaoshuai and
Wang, Xiaogang and Li, Hongsheng},
title = {LIGA-Stereo: Learning LiDAR Geometry
Aware Representations for Stereo-based 3D
Detector},
booktitle = {Proceedings of the IEEE/CVF
International Conference on Computer Vision
(ICCV)},
month = {October},
year = {2021}
}

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) 96.43 % 93.82 % 86.19 %
Car (Orientation) 96.40 % 93.71 % 86.00 %
Car (3D Detection) 81.39 % 64.66 % 57.22 %
Car (Bird's Eye View) 88.15 % 76.78 % 67.40 %
Pedestrian (Detection) 65.59 % 52.18 % 49.29 %
Pedestrian (Orientation) 53.16 % 40.98 % 38.12 %
Pedestrian (3D Detection) 40.46 % 30.00 % 27.07 %
Pedestrian (Bird's Eye View) 44.71 % 34.13 % 30.42 %
Cyclist (Detection) 74.40 % 54.57 % 48.11 %
Cyclist (Orientation) 63.89 % 45.13 % 39.23 %
Cyclist (3D Detection) 54.44 % 36.86 % 32.06 %
Cyclist (Bird's Eye View) 58.95 % 40.60 % 35.27 %
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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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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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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