1 INTRODUCTION

2 CLOSED-WORLD PERSON RE-IDENTIFICATION  
2.1 Feature Representation Learning  
2.2 Deep Metric Learning  
2.3 Ranking Optimization  
2.4 Datasets and Evaluation  

3 OPEN-WORLD PERSON RE-IDENTIFICATION  
3.1 Heterogeneous Re-ID  
3.2 End-to-End Re-ID  
3.3 Semi-supervised and Unsupervised Re-ID  
3.4 Noise-Robust Re-ID  
3.5 Open-set Re-ID and Beyond  

4 AN OUTLOOK: RE-ID IN NEXT ERA  
4.1 mINP: A New Evaluation Metric for Re-ID  
4.2 A New Baseline for Single-/Cross-Modality Re-ID  
4.3 Under-Investigated Open Issues  

5 CONCLUDING REMARKS