Efficient Online Local Metric Adaptation via Negative Samples for Person Re-identification

@article{Zhou2017EfficientOL,
  title={Efficient Online Local Metric Adaptation via Negative Samples for Person Re-identification},
  author={Jiahuan Zhou and Pei Yu and Wei Tang and Ying Wu},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={2439-2447}
}
Many existing person re-identification (PRID) methods typically attempt to train a faithful global metric offline to cover the enormous visual appearance variations, so as to directly use it online on various probes for identity match- ing. However, their need for a huge set of positive training pairs is very demanding in practice. In contrast to these methods, this paper advocates a different paradigm: part of the learning can be performed online but with nominal costs, so as to achieve online… CONTINUE READING
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