layumi / Person_reID_baseline_pytorch

:bouncing_ball_person: Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
https://www.zdzheng.xyz
MIT License
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请问这个项目关联的论文是哪个呢?需要借助论文来理解下代码。 #167

Closed zaiweijian closed 5 years ago

layumi commented 5 years ago

你好。这个baseline结合了挺多论文的。

结果的话,你可以引用

@article{zheng2019joint,
  title={Joint discriminative and generative learning for person re-identification},
  author={Zheng, Zhedong and Yang, Xiaodong and Yu, Zhiding and Zheng, Liang and Yang, Yi and Kautz, Jan},
  journal={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019}
}

random erasing的正则效果:

@article{zhong2017random,
  title={Random erasing data augmentation},
  author={Zhong, Zhun and Zheng, Liang and Kang, Guoliang and Li, Shaozi and Yang, Yi},
  journal={arXiv preprint arXiv:1708.04896},
  year={2017}
}

svdnet 和 triplet net 提出加入 bn层:

@article{DBLP:journals/corr/SunZDW17,
  author    = {Yifan Sun and
               Liang Zheng and
               Weijian Deng and
               Shengjin Wang},
  title     = {SVDNet for Pedestrian Retrieval},
  booktitle   = {ICCV},
  year      = {2017},
}

@article{hermans2017defense,
  title={In Defense of the Triplet Loss for Person Re-Identification},
  author={Hermans, Alexander and Beyer, Lucas and Leibe, Bastian},
  journal={arXiv preprint arXiv:1703.07737},
  year={2017}
}

基础的网络结构:

@article{zheng2018discriminatively,
  title={A discriminatively learned CNN embedding for person reidentification},
  author={Zheng, Zhedong and Zheng, Liang and Yang, Yi},
  journal={ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)},
  volume={14},
  number={1},
  pages={13},
  year={2018},
  publisher={ACM}
}
zaiweijian commented 5 years ago

A DiscriminativeLearned CNN Embedding for Person Re-identification。我看大佬您在知乎上写的,这个项目是在这个论文基础上改进的,请问是不是可以参考下上面的这篇呢?

layumi commented 5 years ago

可以。不过这一篇最早是用matconvnet实现的,当时还没有加入bn层,所以结果有限。

zaiweijian commented 5 years ago

谢谢