To help you better understand the CSCL framework presented in our paper, we provide codes for establishing reliable continuous 2D-to-3D mapping for pedestrian images in both general and cloth-changing ReID datasets, which corresponds to the key CSE module in our paper.
- Python 3.8
- Pytorch 1.11.0
Run
python setup.py install
to compile this project.
General ReID datasets:
Cloth-Changing ReID datasets:
Download the dataset to your local folder. For example, './data/LTCC'
CSE training codes are implemented in
trainer/cse_trainer.py
: train CSE module for ReID models
To train CSE module, you can do
python engine/cse_trainer.py \
--dataset './data/DP3D' \
--epoch 40