research-article

Local Correlation Ensemble with GCN Based on Attention Features for Cross-domain Person Re-ID

Authors:

Viacheslav Voronin,

Shaohua WanAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 19, Issue 2

Article No.: 56, Pages 1 - 22

https://doi.org/10.1145/3542820

Published: 06 February 2023 Publication History

Abstract

Person re-identification (Re-ID) has achieved great success in single-domain. However, it remains a challenging task to adapt a Re-ID model trained on one dataset to another one. Unsupervised domain adaption (UDA) was proposed to migrate a model from a labeled source domain to an unlabeled target domain. The main difference in the cross-domain is different background styles. Although the style transfer approach effectively reduces inter-domain gaps, it ignores the reduction of intra-class differences. Clustering-based pipelines maintain state-of-the-art performance for UDA by learning domain-independent features; however, most existing models do not sufficiently exploit the rich unlabeled samples in target domains due to unsatisfactory clustering. Thus, we propose a novel local correlation ensemble model that focuses on the diversity of intra-class information and the reliability of class centers. Specifically, a pedestrian attention module is proposed to enable the encoder to pay more attention to the person’s features to relieve interference caused by the shared background style. Furthermore, we propose a priority-distance graph convolutional network (PDGCN) module that employs a graph convolutional network network to predict the priority of a node as a class center and then calculates the distance between nodes with high priority values to screen out the class center nodes. Finally, the encoder features (local) and PDGCN features (context-aware) are combined to perform person Re-ID. The results of experiments on the large-scale public Re-ID datasets verified the effectiveness of the proposed method.

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Local Correlation Ensemble with GCN Based on Attention Features for Cross-domain Person Re-ID
1. Computing methodologies

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 19, Issue 2

March 2023

540 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3572860

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Publication History

Published: 06 February 2023

Online AM: 09 June 2022

Accepted: 31 May 2022

Revised: 08 April 2022

Received: 17 December 2021

Published in TOMM Volume 19, Issue 2

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National Natural Science Foundation of China
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