Co-Metric Learning for Person Re-Identification

Figure 2

Flowchart of the co-metric learning framework for person re-identification. Single-view features of training data are firstly decomposed into pseudo two views for learning corresponding metric models. And then ranking list of unlabelled dataset in each view could be generated via distance measurement. Finally, positive and negative pseudo labels that are the top-n and bottom-m samples of ranking list, respectively, and references that are the top-k neighbours of consensual pseudo-labels (marked red) are jointly utilized for metric update.