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. 2025 Aug 11;16:1596408. doi: 10.3389/fneur.2025.1596408

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Copyright © 2025 Yu and Zhu.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Two bar charts compare performance metrics on the AFLW and PoseTrack datasets for different models. Metrics include Accuracy, Recall, F1 Score, and AUC. Models like HRNet, SimpleBaseline, DarkPose, OpenPose, DEKR, PRTR, and an unnamed model labeled “Ours” are shown. “Ours” performs highest in both datasets across all metrics. Performance is measured as a percentage, with the left chart focusing on AFLW and the right on PoseTrack. — Analysis of the performance of SOTA techniques on the AFLW and PoseTrack datasets.