Security and privacy for 6G: A survey on prospective technologies and challenges

VL Nguyen, PC Lin, BC Cheng… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Sixth-generation (6G) mobile networks will have to cope with diverse threats on a space-air-
ground integrated network environment, novel technologies, and an accessible user …

Person re-identification: A retrospective on domain specific open challenges and future trends

A Zahra, N Perwaiz, M Shahzad, MM Fraz - Pattern Recognition, 2023 - Elsevier
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 …

Invariance matters: Exemplar memory for domain adaptive person re-identification

Z Zhong, L Zheng, Z Luo, S Li… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
This paper considers the domain adaptive person re-identification (re-ID) problem: learning
a re-ID model from a labeled source domain and an unlabeled target domain. Conventional …

Self-similarity grou**: A simple unsupervised cross domain adaptation approach for person re-identification

Y Fu, Y Wei, G Wang, Y Zhou, H Shi… - proceedings of the …, 2019 - openaccess.thecvf.com
Abstract Domain adaptation in person re-identification (re-ID) has always been a
challenging task. In this work, we explore how to harness the similar natural characteristics …

Unsupervised person re-identification via softened similarity learning

Y Lin, L **e, Y Wu, C Yan… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
Person re-identification (re-ID) is an important topic in computer vision. This paper studies
the unsupervised setting of re-ID, which does not require any labeled information and thus is …

Image-image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification

W Deng, L Zheng, Q Ye, G Kang… - Proceedings of the …, 2018 - openaccess.thecvf.com
Person re-identification (re-ID) models trained on one domain often fail to generalize well to
another. In our attempt, we present a``learning via translation''framework. In the baseline, we …