Abstract Person Re-Identification (ReID) is an essential technology for matching a person
across non-overlap** cameras. It has attracted increasing attention in recent years due to …

Due to the limited utilization of temporal relations in video re-id, the frame-level attention
regions of mainstream methods are partial and highly similar. To address this problem, we …

In video surveillance, pedestrian retrieval (also called person reidentification) is a critical
task. This task aims to retrieve the pedestrian of interest from nonoverlap** cameras …

Video person re-identification (V-ReID) can leverage rich spatial-temporal information
embedded in sequence data to achieve better accuracy. However, it is vulnerable to the …

The video-based person re-identification (ReID) aims to identify the given pedestrian video
sequence across multiple non-overlap** cameras. To aggregate the temporal and spatial …

Pedestrian attribute recognition (PAR) and re-identification (ReID) are important works in the
area of computer vision, which are widely used in intelligent surveillance and are of great …

Single-modal object re-identification (ReID) faces great challenges in maintaining
robustness within complex visual scenarios. In contrast multi-modal object ReID utilizes …

Video-based person re-identification (Re-ID) is a prominent computer vision topic due to its
wide range of video surveillance applications. Most existing methods utilize spatial and …

In recent years, the Transformer architecture has shown its superiority in the video-based
person re-identification task. Inspired by video representation learning, these methods …