Person Re-identification through Clustering and Partial Label Smoothing Regularization

@inproceedings{Ainam2019PersonRT,
  title={Person Re-identification through Clustering and Partial Label Smoothing Regularization},
  author={Jean-Paul Ainam and Ke Qin and Guisong Liu and Guangchun Luo},
  booktitle={ICSIM 2019},
  year={2019}
}
In this paper, we propose a new label smoothing regularization scheme for person re-identification. We first use an unsupervised method for discriminative learning representation. We apply a clustering algorithm on the learned feature to partition the training set into k groups of equal variance and derive a shared space for similar images. Secondly, a GAN model is fed with each cluster to produce samples with relatively similar features to the original space. Our method consists of assigning… CONTINUE READING

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