LUPerson-NL
Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL)
The repository is for our CVPR2022 paper Large-Scale Pre-training for Person Re-identification with Noisy Labels.
LUPerson-NL Dataset
LUPerson-NL is currently the largest noisy annotated Person Re-identification dataset without humuan labelling efforts, which is used for Pre-training. LUPerson-NL consists of 10M images of over 430K identities extracted from 21K street-view videos and covers a much diverse range of capturing environments.
Details can be found at ./LUP-NL.
Pre-trained Models
Model | link |
---|---|
ResNet50 | R50 code:pr50 |
ResNet101 | R101 code:r101 |
ResNet152 | R152 code:r152 |
Finetuned Results
For MGN with ResNet50:
Dataset | mAP | cmc1 | link |
---|---|---|---|
MSMT17 | 68.0 | 86.0 | - |
DukeMTMC | 84.3 | 92.0 | - |
Market1501 | 91.9 | 96.6 | - |
CUHK03-L | 80.4 | 80.9 | - |
For MGN with ResNet101:
Dataset | mAP | cmc1 | path |
---|---|---|---|
MSMT17 | 70.8 | 87.1 | - |
DukeMTMC | 85.5 | 92.8 | - |
Market1501 | 92.5 | 96.9 | - |
CUHK03-L | 80.5 | 81.2 | - |
For MGN with ResNet152:
Dataset | mAP | cmc1 | path |
---|---|---|---|
MSMT17 | 71.6 | 87.5 | - |
DukeMTMC | 85.6 | 92.4 | - |
Market1501 | 92.7 | 96.8 | - |
CUHK03-L | 80.6 | 81.2 | - |
Citation
If you find this code useful for your research, please cite our paper.
@article{fu2020unsupervised,
title={Unsupervised Pre-training for Person Re-identification},
author={Fu, Dengpan and Chen, Dongdong and Bao, Jianmin and Yang, Hao and Yuan, Lu and Zhang, Lei and Li, Houqiang and Chen, Dong},
journal={Proceedings of the IEEE conference on computer vision and pattern recognition},
year={2021}
}
@article{fu2022large,
title={Large-Scale Pre-training for Person Re-identification with Noisy Labels},
author={Fu, Dengpan and Chen, Dongdong and Yang, Hao and Bao, Jianmin and Yuan, Lu and Zhang, Lei and Li, Houqiang and Wen, Fang and Chen, Dong},
journal={arXiv preprint arXiv:2203.16533},
year={2022}
}