Awesome
HRCN
This repository contains PyTorch codes for the ICCV2021 paper "Heterogeneous Relational Complement for Vehicle Re-identification"
Installation
Requirements
- Linux with python 3.6
- pytorch 1.4.0
- torchvision 0.5.0
- cudatoolkit 10.0
Set up with Conda
cd HRCN
conda env create -f hrcn.yml
conda activate hrcn
pip install -r requirements.txt
Training and Evaluating
Replace the [source_link] with the dataset directory in dataset_soft_link.sh.
Download trained models into the directory model_weight.
cd HRCN
sh dataset_soft_link.sh
# Train in VehicleID, VeRi or VERIWild
sh trainVehicleID.sh
sh trainVeRi.sh
sh trainVERIWild.sh
# Evaluate in VehicleID, VeRi or VERIWild
sh testVehicleID.sh
sh testVeRi.sh
sh testVERIWild.sh
Citation
@InProceedings{Zhao_2021_ICCV,
author = {Zhao, Jiajian and Zhao, Yifan and Li, Jia and Yan, Ke and Tian, Yonghong},
title = {Heterogeneous Relational Complement for Vehicle Re-Identification},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021},
pages = {205-214}
}
Acknowledgment
This repository is based on the implementation of fast-reid.