Method

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation [st] [Disp R-CNN]
https://github.com/zju3dv/disprcnn

Submitted on 25 Jun. 2020 10:03 by
Yiming Xie (Zhejiang University)

Running time:0.42 s
Environment:GPU @ 2.5 Ghz (Python + C/C++)

Method Description:
with stereo image only during both training and
inference
Parameters:
as detailed in the paper
Latex Bibtex:
@inproceedings{sun2020disprcnn,
title={Disp R-CNN: Stereo 3D Object Detection
via Shape Prior Guided Instance Disparity
Estimation},
author={Sun, Jiaming and Chen, Linghao and Xie,
Yiming and
Zhang, Siyu and Jiang, Qinhong and Zhou,
Xiaowei and Bao, Hujun},
booktitle={CVPR},
year={2020}
}

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) 93.26 % 82.57 % 68.20 %
Car (Orientation) 93.02 % 81.70 % 67.16 %
Car (3D Detection) 58.55 % 37.93 % 31.95 %
Car (Bird's Eye View) 73.87 % 52.37 % 43.67 %
Pedestrian (Detection) 68.93 % 51.36 % 46.79 %
Pedestrian (Orientation) 60.00 % 43.76 % 39.55 %
Pedestrian (3D Detection) 31.05 % 21.98 % 18.67 %
Pedestrian (Bird's Eye View) 36.06 % 25.36 % 21.62 %
Cyclist (Detection) 58.26 % 42.23 % 36.88 %
Cyclist (Orientation) 50.64 % 35.76 % 30.95 %
Cyclist (3D Detection) 39.72 % 23.75 % 20.47 %
Cyclist (Bird's Eye View) 43.41 % 26.46 % 22.46 %
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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