Method

SINet: A Scale-Insensitive Convolutional Neural Network for Fast Vehicle Detection [SINet_PVA]
https://github.com/xw-hu/SINet

Submitted on 4 May. 2017 06:47 by
Xiaowei HU (The Chinese University of Hong Kong)

Running time:0.11 s
Environment:TITAN X GPU

Method Description:
Parameters:
Basic Network: PVANET
Latex Bibtex:
@article{hu2019sinet,
title={SINet: A Scale-insensitive Convolutional
Neural Network for Fast Vehicle Detection},
author={Hu, Xiaowei and Xu, Xuemiao and Xiao,
Yongjie and Chen, Hao and He, Shengfeng and Qin,
Jing and Heng, Pheng-Ann},
journal={IEEE Transactions on Intelligent
Transportation Systems},
volume={20},
number={3},
pages={1010--1019},
year={2019},
publisher={IEEE}
}

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) 92.72 % 89.86 % 76.47 %
This table as LaTeX

2D object detection results.
This figure as: png eps pdf txt gnuplot




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