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To address these challenges, we propose GCAT-Net, a novel framework that integrates Semantic Graph Convolutional Network (SemGCN), Criss-Cross Attention (CCA) and Transformer Encoder to effectively capture both local and global dependencies in human joint relationships. GCAT-Net\u2019s ability to combine these components allows it to accurately predict 3D poses, even in complex environments, making it suitable for a wide range of real-world applications. Experimental results demonstrate that GCAT-Net outperforms existing methods on multiple benchmark datasets. The model exhibits strong generalizability, handling complex poses and occlusions effectively, which highlights its robustness and adaptability. GCAT-Net not only improves estimation accuracy but also contributes to the understanding of human motion by enhancing feature extraction at both local and global levels. <\/jats:p>","DOI":"10.1142\/s0218126625502524","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T09:16:23Z","timestamp":1740129383000},"source":"Crossref","is-referenced-by-count":1,"title":["A Robust Framework for 3D Human Pose Estimation Using Semantic Graph Convolution, Criss-Cross Attention and Transformer Encoder"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4716-5665","authenticated-orcid":false,"given":"Yu","family":"Hou","sequence":"first","affiliation":[{"name":"Department of Physical Education, Kunsan National University, Jeollabuk-do, Gunsan-si 54150, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3679-8387","authenticated-orcid":false,"given":"Cenyue","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Physical Education, Kunsan National University, Jeollabuk-do, Gunsan-si 54150, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8469-0481","authenticated-orcid":false,"given":"He","family":"Peng","sequence":"additional","affiliation":[{"name":"Department of Physical Education, Kunsan National University, Jeollabuk-do, Gunsan-si 54150, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7059-3614","authenticated-orcid":false,"given":"Tong","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Physical Education, Kunsan National University, Jeollabuk-do, Gunsan-si 54150, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9820-1160","authenticated-orcid":false,"given":"Haoxuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Tiangong\u00a0University, Tianjin 300382, P. 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