Some minor changes, such as class name changing, remove extra blank line, etc. |
||
---|---|---|
.. | ||
configs | ||
partialreid | ||
README.md | ||
train_net.py |
README.md
DSR in FastReID
Deep Spatial Feature Reconstruction for Partial Person Re-identification
Lingxiao He, Xingyu Liao
Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification
Lingxiao He, Xingyu Liao
News!
[1] The old_version code can be check in old_version, you can obtain the same result published in paper, and the new version code is updating, please waiting!
Installation
First install FastReID, and then put Partial Datasets in directory datasets. The whole framework of FastReID-DSR is

and the detail you can refer to
Datasets
The datasets can find in Google Drive
PartialREID---gallery: 300 images of 60 ids, query: 300 images of 60 ids
PartialiLIDS---gallery: 119 images of 119 ids, query: 119 images of 119 ids
OccludedREID---gallery: 1,000 images of 200 ids, query: 1,000 images of 200 ids
Training and Evaluation
To train a model, run:
python3 projects/PartialReID/train_net.py --config-file <config.yaml>
For example, to train the re-id network with IBN-ResNet-50 Backbone one should execute:
CUDA_VISIBLE_DEVICES='0,1,2,3' python3 projects/PartialReID/train_net.py --config-file 'projects/PartialReID/configs/partial_market.yml'
Results
Method | PartialREID | OccludedREID | PartialiLIDS |
---|---|---|---|
Rank@1 (mAP) | Rank@1 (mAP) | Rank@1 (mAP) | |
DSR (CVPR’18) | 73.7(68.1) | 72.8(62.8) | 64.3(58.1) |
FPR (ICCV'19) | 81.0(76.6) | 78.3(68.0) | 68.1(61.8) |
FastReID-DSR | 82.7(76.8) | 81.6(70.9) | 73.1(79.8) |
Citing DSR and Citing FPR
If you use DSR or FPR, please use the following BibTeX entry.
@inproceedings{he2018deep,
title={Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach},
author={He, Lingxiao and Liang, Jian and Li, Haiqing and Sun, Zhenan},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2018}
}
@inproceedings{he2019foreground,
title={Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification},
author={He, Lingxiao and Wang, Yinggang and Liu, Wu and Zhao, He and Sun, Zhenan and Feng, Jiashi},
booktitle={IEEE International Conference on Computer Vision (ICCV)},
year={2019}
}