https://github.com/tinyvision/solider-personsearch
https://github.com/tinyvision/solider-personsearch
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/tinyvision/solider-personsearch
- Owner: tinyvision
- Created: 2023-03-27T11:28:09.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2023-04-03T07:45:34.000Z (almost 3 years ago)
- Last Synced: 2025-03-27T01:23:45.806Z (11 months ago)
- Language: Python
- Size: 2.83 MB
- Stars: 13
- Watchers: 1
- Forks: 7
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
# SOLIDER on [Person Search]
[](https://paperswithcode.com/sota/person-search-on-cuhk-sysu?p=beyond-appearance-a-semantic-controllable)
[](https://paperswithcode.com/sota/person-search-on-prw?p=beyond-appearance-a-semantic-controllable)
This repo provides details about how to use [SOLIDER](https://github.com/tinyvision/SOLIDER) pretrained representation on person search task.
We modify the code from [SeqNet](https://github.com/serend1p1ty/SeqNet), and you can refer to the original repo for more details.
## Installation and Datasets
Details of installation and dataset preparation can be found in [SeqNet](https://github.com/serend1p1ty/SeqNet).
## Prepare Pre-trained Models
You can download models from [SOLIDER](https://github.com/tinyvision/SOLIDER), or use [SOLIDER](https://github.com/tinyvision/SOLIDER) to train your own models.
Before training, you should convert the models first.
```bash
python convert_model.py path/to/SOLIDER/log/lup/swin_tiny/checkpoint.pth path/to/SOLIDER/log/lup/swin_tiny/checkpoint_tea.pth
```
## Training
We utilize 1 GPU for training. Please modify the `ckpt` and `OUTPUT_DIR` in the bash file.
```bash
sh run.sh
```
## Performance
| Method | Model | CUHK-SYSU
(mAP/R1) | PRW
(mAP/R1) |
| ------ | :---: | :---: | :---: |
| SOLIDER | Swin Tiny | 94.91/95.72 | 56.84/86.78 |
| SOLIDER | Swin Small | 95.46/95.79 | 59.84/86.73 |
| SOLIDER | Swin Base | 94.93/95.52 | 59.72/86.83 |
- We use the pretrained models from [SOLIDER](https://github.com/tinyvision/SOLIDER).
- The semantic weight is set to 0.6 in these experiments.
## Citation
If you find this code useful for your research, please cite our paper
```
@inproceedings{chen2023beyond,
title={Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks},
author={Weihua Chen and Xianzhe Xu and Jian Jia and Hao Luo and Yaohua Wang and Fan Wang and Rong Jin and Xiuyu Sun},
booktitle={The IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2023},
}
```