Skip to content
/ HPGN Public

Implementation code:Exploring spatial significance via hybrid pyramidal graph network for vehicle re-identification

License

Notifications You must be signed in to change notification settings

muzishen/HPGN

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

HPGN

T-ITS-2021:Exploring spatial significance via hybrid pyramidal graph network for vehicle re-identification

HPGN

Weights link

Please use the link below to get trained weights.

Baidu Cloud

Training

python3 main.py  --mode train

Testing

python3 main.py  --mode evaluate

Citation

If you find this code useful for your research, please cite our paper

@article{shen2021exploring,
  title={Exploring spatial significance via hybrid pyramidal graph network for vehicle re-identification},
  author={Shen, Fei and Zhu, Jianqing and Zhu, Xiaobin and Xie, Yi and Huang, Jingchang},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2021},
  publisher={IEEE}
}

About

Implementation code:Exploring spatial significance via hybrid pyramidal graph network for vehicle re-identification

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Languages