Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification (AAAI'24)

Introduction

This is the official repo for our AAAI 2024 paper "DACS".

Prerequisites

• CUDA>=11.7

• At least two TITAN X GPUs

• Other necessary packages listed in requirements.txt

• Download ViT pre-trained model and put it under "./checkpoints"

• Training Data

  (Market-1501, DukeMTMC-reID and MSMT-17. You can download these datasets from Zhong's repo)

  Unzip all datasets and ensure the file structure is as follow:

  DACS/data    
  │
  └───market1501 OR dukemtmc OR msmt17
       │   
       └───DukeMTMC-reID OR Market-1501-v15.09.15 OR MSMT17_V1
           │   
           └───bounding_box_train
           │   
           └───bounding_box_test
           | 
           └───query
           │   
           └───list_train.txt (only for MSMT-17)
           | 
           └───list_query.txt (only for MSMT-17)
           | 
           └───list_gallery.txt (only for MSMT-17)
           | 
           └───list_val.txt (only for MSMT-17)
  

Usage

See run.sh for details.

Supplementary

The supplementary material of our paper is located at "figures/supp.pdf"

How to Cite

@inproceedings{yang2024diversity,
  title={Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification},
  author={Yang, Fengxiang and Zhong, Zhun and Luo, Zhiming and He, Yifan and Li, Shaozi and Sebe, Nicu},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={6},
  pages={6477--6485},
  year={2024}
}

Contact Us

Email: yangfx@stu.xmu.edu.cn