BBAuthors: Wu, D.; Advisor: -; Participants: Yang, H.; Huang, D.; Yuan, C.; Qin, X.; Zhao, Y.; Zhao, X.; Sun, J. (2019)
Person re-identi cation (PReID) has received increasing attention due to it being an important role in intelligent surveillance. Many state-of-the-art PReID methods are part-based deep models. Most of these models focus on learning the part feature representation of a person's body from the horizontal direction. However, the feature representation of the body from the vertical direction is usually ignored. In addition, the relationships between these part features and different feature channels are not considered. In this paper, we introduce a multi-branch deep model for PReID. Speci cally, the model consists of ve branches. Among the ve branches, two branches learn the part feature... 
