Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …

Person re-identification aims to retrieve persons in highly varying settings across different
cameras and scenarios, in which robust and discriminative representation learning is …

This study proposes a simple but strong baseline for deep person re-identification (ReID).
Deep person ReID has achieved great progress and high performance in recent years …

When considering person re-identification (re-ID) as a retrieval process, re-ranking is a
critical step to improve its accuracy. Yet in the re-ID community, limited effort has been …

The superiority of deeply learned pedestrian representations has been reported in very
recent literature of person re-identification (re-ID). In this article, we consider the more …

Person re-identification is a challenging retrieval task that requires matching a person's
acquired image across non-overlapping camera views. In this paper we propose an effective …

Visible thermal person re-identification (VT-REID) is a task of matching person images
captured by thermal and visible cameras, which is an extremely important issue in night-time …

Person re-identification is widely studied in visible spectrum, where all the person images
are captured by visible cameras. However, visible cameras may not capture valid …

The person re-identification task requires to robustly estimate visual similarities between
person images. However, existing person re-identification models mostly estimate the …

Cross-modality person re-identification between the thermal and visible domains is
extremely important for night-time surveillance applications. Existing works in this filed …