Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

This PyTorch code is proposed in our paper [1]. A Chinese blog is available in 再见，迁移学习？可解释和泛化的行人再辨识.

• 2/7/2020: An important update: include a pre-training function for a better initialization, so that the results are now more stable.
• 11/26/2020: Include the IBN-Net as backbone, and the RandPerson dataset.

• Pytorch (>1.0)
• sklearn
• scipy

Download some public datasets (e.g. Market-1501, DukeMTMC-reID, CUHK03-NP, MSMT) on your own, extract them in some folder, and then run the followings.

python main.py --dataset market --testset duke[,market,msmt] [--data-dir ./data] [--exp-dir ./Exp]

For more options, run "python main.py --help". For example, if you want to use the ResNet-152 as backbone, specify "-a resnet152". If you want to train on the whole dataset (as done in our paper for the MSMT17), specify "--combine_all".

python main.py --dataset market --testset duke[,market,msmt] [--data-dir ./data] [--exp-dir ./Exp] --evaluate

• Updated performance (%) of QAConv under direct cross-dataset evaluation without transfer learning or domain adaptation:

Note: results are obtained by neck=64, batch_size=8, lr=0.005, epochs=15, and step_size=10 (except for RandPerson epochs=4 and step_size=2), trained on one single GPU. By this setting the traininig and testing time is much reduced.

• Performance (%) of QAConv in the ECCV paper, with ResNet-152 under direct cross-dataset evaluation:

• QAConv_ResNet50_MSMT
• QAConv_ResNet152_MSMT

The above pre-trained models can also be downloaded from Baidu (access code: 52cv), thanks to 52CV.

Shengcai Liao
Inception Institute of Artificial Intelligence (IIAI)
[email protected]

[1] Shengcai Liao and Ling Shao, "Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting." In the 16th European Conference on Computer Vision (ECCV), 23-28 August, 2020.

@inproceedings{Liao-ECCV2020-QAConv,
title={{Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting}},
author={Shengcai Liao and Ling Shao},
booktitle={European Conference on Computer Vision (ECCV)},
year={2020}
}