Abstract Pedestrian Attribute Recognition (PAR) is an important task in computer vision
community and plays an important role in practical video surveillance. The goal of this paper …

Existing text-based person retrieval datasets often have relatively coarse-grained text
annotations. This hinders the model to comprehend the fine-grained semantics of query …

In civilian video security monitoring, retrieving and tracking a person of interest often rely on
witness testimony and their appearance description.| Deployed systems rely on a large …

Nowadays, video surveillance systems are widely deployed in public areas. However, in the
unreachable corner of surveillance cameras, it still seems impossible to find the suspects …

Person search has become one of the most critical and challenging applications in today's
video surveillance systems. It helps in locating a person in surveillance videos, which is …

Abstract Global feature based Pedestrian Attribute Recognition (PAR) models are often
poorly localized when using Grad-CAM for attribute response analysis, which has a …

Skeleton-based action recognition is a prominent research area that provides a concise
representation of human motion. However, real-world scenarios pose challenges to the …

Pedestrian attribute recognition (PAR) poses a significant challenge but holds practical
significance in various security applications, including surveillance. In the scope of the …

We introduce a new framework, dubbed Cerberus, for attribute-based person re-
identification (reID). Our approach leverages person attribute labels to learn local and global …

The fine-grained attribute descriptions can significantly supplement the valuable semantic
information for person image, which is vital to the success of person re-identification (ReID) …