Person re-identification (Re-ID) aims to match the image frames which contain the same
person in the surveillance videos. Most of the Re-ID algorithms conduct supervised training …

Learning effective feature representations with deep convolutional neural network (CNN)
and metric learning methods to distinguish pedestrians is the key to the success of recent …

Person re-identification (person re-ID) aims at matching target person (s) grabbed from
different and non-overlapping camera views. It plays an important role for public safety and …

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) is the task of associating the image patches of the identical
person across disjoint cameras, which is a very challenging topic in computer vision …

Existing person re-identification (Re-ID) methods principally deploy the ImageNet-1K
dataset for model initialization, which inevitably results in sub-optimal situations due to the …

Person re-identification (Person Re-ID) is a research direction on tracking and identifying
people in surveillance camera systems with non-overlapping camera perspectives. Despite …

Abstract Most existing Re-IDentification (Re-ID) methods are highly dependent on precise
bounding boxes that enable images to be aligned with each other. However, due to the …

One of the important Internet-of-Things applications is to use image and video to realize
automatic people monitoring, surveillance, tracking, and reidentification (Re-ID). Despite …

Person re-identification (Re-ID) is a crucial technology for intelligent security in Internet of
Things (IoT) systems. Recently, unsupervised learning has been widely used for person Re …