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ddan's Introduction

Dual Distribution Alignment Network for Generalizable Person Re-Identification

This resposity is the official implementation of our AAAI2021 Paper.

Dependent

Python 3.7.5
PyTorch == 1.3.1

Datasets

You maybe need the CUHK-SYSU and the iLIDS. Other datasets are available from the original author's open source website.

Usage

train/test

bash run.sh

Model

Download the DDAN model.

Citations

If our paper helps your research, please cite it in your publications:

@inproceedings{AAAI: 2021,
Author={Peixian Chen, Pingyang Dai, Jianzhuang Liu, Feng Zheng, Minglinag Xu, Qi Tian, Rongrong Ji.},
Title={Dual Distribution Alignment Network for Generalizable Person Re-Identification},
Booktitle={Thirty-Fifth AAAI Conference on Artificial Intelligence},
Year={2021}, Accept}

ddan's People

Contributors

Stargazers

Watchers

Forkers

aldrichall kevinbro96 chenshen03

ddan's Issues

Cannot reproduce the results in the paper

Hi, I run your code directly but only achieve
Viper prid grid ilids
map rank-1 map rank-1 map rank-1 map rank-1
52.6 48.1 53.6 48.4 52.2 50.0 79.3 76.0

Can you explain the reason?

关于数据格式

请问按照您的读取数据的代码，训练数据和测试数据的存储目录和图片命名规则应该是什么样的？

code about DDAN+DualNorm

Can you share the code of the model "DDAN+DualNorm " plz?

Wrong evaluation protocols for ViPeR

Hi, your evaluation protocols on ViPeR is wrong.
https://github.com/Pealing/DDAN/blob/main/reid/evaluators.py#L20
else:
t = gallery_idx
gallery_idx=query_idx
query_idx = gallery_idx
The right way is swapping the query and gallery sets. But you only swap the query_id and gallery_id, which are actually the same.
And using your code, the two swapping results are just the same.

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