Code for paper "Structure-Regularized Attention for Deformable Object Representation".

The code contains the ResNet50-StRA network for person re-identification task and the corresponding configurations to reproduce our results.

To install requirements:

pip install -r requirements.txt

The reported results are trained and evaluated based on the existing person ReID framework: https://github.com/KaiyangZhou/deep-person-reid.

To reproduce the reported results, please pull from the above deep-person-reid repository (version 0.9.1) and download the datasets following the instructions. Then integrate with our network code:

mv models ./deep-person-reid/torchreid

To train our StRA-ResNet50 on Market-1501 dataset:

python train.py

To train on different datasets, change different dataset sources in train.py.

Simply running the following code will give the reported results on Market-1501 dataset:

python eval.py

By downloading our pre-trained model and running the evaluation code, the followng results will be obtained. And the result reported in the paper is the mean of 3 runs.

The checkpoint model on Market-1501 dataset can be found at https://drive.google.com/file/d/1oXLY60iX8Vkbp-iTlrrzzkrFjME1Esun/view?usp=sharing.