Awesome
SOLIDER on [Person Search]
This repo provides details about how to use SOLIDER pretrained representation on person search task. We modify the code from 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.
Prepare Pre-trained Models
You can download models from SOLIDER, or use SOLIDER to train your own models. Before training, you should convert the models first.
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.
sh run.sh
Performance
Method | Model | CUHK-SYSU<br>(mAP/R1) | PRW<br>(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.
- 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},
}