Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …

A proposed method, Enhancement, integration, and Expansion, aims to activate the
representation of detailed features for occluded person re-identification. Region and context …

Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

Person Re-Identification is a challenging task that aims to retrieve all instances of a query
image across a system of non-overlapping cameras. Due to the various extreme changes of …

Existing person re-identification methods mainly focus on searching the target person across
disjoint camera views in a short period of time. With this setting, these methods rely on the …

Occluded person re-identification (Re-ID) focuses on addressing the occlusion problem
when retrieving the person of interest across non-overlapping cameras. With the increasing …

Person re-identification (Re-ID) subject to loss of detailed information (sacrificing certain
intricate body details) in samples caused by conventional regularization algorithms and …

Abstract Vehicle Re-Identification (V-ReID) is a critical task that associates the same vehicle
across images from different camera viewpoints. Many works explore attribute clues to …

Salient Object Detection (SOD) aims to identify and segment the most prominent objects in
images. Advanced SOD methods often utilize various Convolutional Neural Networks (CNN) …