Corpus ID: 4558083

Graph Correspondence Transfer for Person Re-identification

@article{Zhou2018GraphCT,
  title={Graph Correspondence Transfer for Person Re-identification},
  author={Qin Zhou and Heng Fan and Shibao Zheng and Hang Su and Xinzhe Li and Shuang Wu and Haibin Ling},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.00242}
}
  • Qin Zhou, Heng Fan, +4 authors Haibin Ling
  • Published 2018
  • Computer Science
  • ArXiv
  • In this paper, we propose a graph correspondence transfer (GCT) approach for person re-identification. Unlike existing methods, the GCT model formulates person re-identification as an off-line graph matching and on-line correspondence transferring problem. In specific, during training, the GCT model aims to learn off-line a set of correspondence templates from positive training pairs with various pose-pair configurations via patch-wise graph matching. During testing, for each pair of test… CONTINUE READING

    Figures, Tables, and Topics from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 14 CITATIONS

    Robust and Efficient Graph Correspondence Transfer for Person Re-identification

    • Qin Zhou, Heng Fan, +4 authors Haibin Ling
    • Mathematics, Medicine, Computer Science
    • IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    • 2019
    VIEW 10 EXCERPTS
    CITES METHODS & BACKGROUND

    Vehicle Re-Identification With Viewpoint-Aware Metric Learning

    VIEW 1 EXCERPT
    CITES BACKGROUND

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 38 REFERENCES

    Person Re-Identification with Correspondence Structure Learning

    VIEW 12 EXCERPTS
    HIGHLY INFLUENTIAL

    Sample-Specific SVM Learning for Person Re-identification

    Person Re-Identification with Discriminatively Trained Viewpoint Invariant Dictionaries

    VIEW 1 EXCERPT

    Transferring a semantic representation for person re-identification and search

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Similarity learning on an explicit polynomial kernel feature map for person re-identification

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Similarity Learning with Spatial Constraints for Person Re-identification

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Fast Person Re-identification via Cross-Camera Semantic Binary Transformation

    VIEW 3 EXCERPTS

    Unsupervised Salience Learning for Person Re-identification

    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Deep Ranking for Person Re-Identification via Joint Representation Learning

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL