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Dual-Stream Guided-Learning via a Priori Optimization for Person Re-identification

Authors:

Jianqiang Zhao,

Liqin HuangAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 4

Article No.: 117, Pages 1 - 22

https://doi.org/10.1145/3447715

Published: 13 January 2022 Publication History

Abstract

The task of person re-identification (re-ID) is to find the same pedestrian across non-overlapping camera views. Generally, the performance of person re-ID can be affected by background clutter. However, existing segmentation algorithms cannot obtain perfect foreground masks to cover the background information clearly. In addition, if the background is completely removed, some discriminative ID-related cues (i.e., backpack or companion) may be lost. In this article, we design a dual-stream network consisting of a Provider Stream (P-Stream) and a Receiver Stream (R-Stream). The R-Stream performs an a priori optimization operation on foreground information. The P-Stream acts as a pusher to guide the R-Stream to concentrate on foreground information and some useful ID-related cues in the background. The proposed dual-stream network can make full use of the a priori optimization and guided-learning strategy to learn encouraging foreground information and some useful ID-related information in the background. Our method achieves Rank-1 accuracy of 95.4% on Market-1501, 89.0% on DukeMTMC-reID, 78.9% on CUHK03 (labeled), and 75.4% on CUHK03 (detected), outperforming state-of-the-art methods.

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Cited By

Wu JHuang YGao MNiu YYang MGao ZZhao JWooldridge MDy JNatarajan S(2024)Selective and orthogonal feature activation for pedestrian attribute recognitionProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v38i6.28419(6039-6047)Online publication date: 20-Feb-2024
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Index Terms

Dual-Stream Guided-Learning via a Priori Optimization for Person Re-identification
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Visual content-based indexing and retrieval

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Published In

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

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 17, Issue 4

November 2021

529 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3492437

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Publication History

Published: 13 January 2022

Accepted: 01 January 2021

Revised: 01 January 2021

Received: 01 July 2020

Published in TOMM Volume 17, Issue 4

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https://dl.acm.org/doi/10.1609/aaai.v38i6.28419
Xiang CWu XHe JYuan ZHe T(2024)Person in Uniforms Re-IdentificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/370383921:2(1-23)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3703839
Wu TZhang SChen DHu H(2024)Text-and-Image Learning Transformer for Cross-Modal Person Re-IdentificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/368616021:1(1-18)Online publication date: 15-Oct-2024
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Wu JHuang YGao MGao ZZhao JZhang HZhang A(2024)A Two-Stream Hybrid Convolution-Transformer Network Architecture for Clothing-Change Person Re-IdentificationIEEE Transactions on Multimedia10.1109/TMM.2023.333156926(5326-5339)Online publication date: 2024
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