This is the codebase for our ACM MM 2022 paper.
datasets
└── cuhkpedes
├── captions.json
└── imgs
├── cam_a
├── cam_b
├── CUHK01
├── CUHK03
├── Market
├── test_query
└── train_query
└──icfgpedes
├── ICFG-PEDES.json
└── ICFG_PEDES
├── test
└── train
wget https://dl.fbaipublicfiles.com/deit/deit_small_distilled_patch16_224-649709d9.pthpython processed_data_singledata_CUHK.py
python processed_data_singledata_ICFG.pypython train_mydecoder_pixelvit_txtimg_3_bert.pyIf you find this project useful for your research, please use the following BibTeX entry.
@inproceedings{shao2022learning,
title={Learning Granularity-Unified Representations for Text-to-Image Person Re-identification},
author={Shao, Zhiyin and Zhang, Xinyu and Fang, Meng and Lin, Zhifeng and Wang, Jian and Ding, Changxing},
booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
year={2022}
}
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