Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification

@article{Xiao2016LearningDF,
  title={Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification},
  author={Tong Xiao and Hongsheng Li and Wanli Ouyang and Xiaogang Wang},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={1249-1258}
}
Learning generic and robust feature representations with data from multiple domains for the same problem is of great value, especially for the problems that have multiple datasets but none of them are large enough to provide abundant data variations. In this work, we present a pipeline for learning deep feature representations from multiple domains with Convolutional Neural Networks (CNNs). When training a CNN with data from all the domains, some neurons learn representations shared across… CONTINUE READING
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Bitscalable deep hashing with regularized similarity learning for image retrieval and person re-identification

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