Paper
21 December 2023 Person re-identification based on spectral nonlocal block and multiscale attention pyramid
Mengwei Sun
Author Affiliations +
Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129701S (2023) https://doi.org/10.1117/12.3012216
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China
Abstract
Due to the complexity of the person re-identification scene, it is easy to be affected by visual changes such as illumination, occlusion, posture, etc, which makes the extracted person features will be insufficient and feature discrimination is poor, which in turn will lead to low retrieval accuracy. To address the above problems, a multi-scale attention pyramid network (SOAPNet) based on non-local block guidance of the spectral is proposed. First, the atlas non-local blocks are introduced into ResNet50 to capture remote dependencies more robustly and flexibly, so as to realize a wider range of information perception in the feature extraction stage; then, the multi-scale attention pyramid network is introduced into ResNet50, so that the model can focus more on the most critical and discriminative information in the person images, and this multi-scale attention strategy effectively solves the problem of The problem of insufficient features and poor discrimination in the person re-identification task, which enables the model to better distinguish person with different identities and extract more robust features. Experiments on Market1501, MSMT17, and DukeReID show that Rank1 is improved by 0.7%, 0.9%, and 1.2%, respectively, and mAP is improved by 0.5%, 1.0%, and 1.4%, respectively. The proposed method can significantly solve the above problems.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Mengwei Sun "Person re-identification based on spectral nonlocal block and multiscale attention pyramid", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129701S (21 December 2023); https://doi.org/10.1117/12.3012216
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KEYWORDS
Feature extraction

Education and training

Spatial learning

Matrices

Visualization

Ablation

Data modeling

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