Learning Feature Fusion for Unsupervised Domain Adaptive Person Re-identification

[news!] [2022.7.27] Our paper is accepted by ICPR2022 oral ! URL

Requirements

• Ubuntu 18.04
• gcc version 7.5.0
• Python 3.8.5
• Pytorch 1.8.1
• NVIDIA GPU : two GeForce RTX 2080Ti
• Anaconda 4.9.2
• CUDA 10.2

Weights

Download the pre-training weights and fine-tuning weights in Baidu Netdisk：lf2m.

Running

step 1 Source-domain pre-training

# for example, duke-to-market
python source_pretrain.py -ds duke -dt market --data-dir PATH/TO/DATA --logs-dir PATH/TO/SAVE/CHECKPOINTS

step 2 Target-domain fine-tuning

# for example, duke-to-market
python target_train.py -dt market --data-dir PATH/TO/DATA --logs-dir PATH/TO/SAVE/CHECKPOINTS

step 3 Evaluate in the target domain

# for example, duke-to-market
python model_test.py -dt market --data-dir PATH/TO/DATA --resume PATH/TO/CHECKPOINTS

Experiments

Acknowledgement

Our code is based on open-reid and MEB-Net.