SAGCN: Self-Attention Graph Convolutional Network for Human Pose Embedding

SAGCN: Self-Attention Graph Convolutional Network for Human Pose Embedding

Accurate human pose embedding is crucial for action recognition. While traditional convolutional neural networks (CNNs) have advanced pose feature extraction, they struggle to model structural relationships and long-range dependencies between keypoints, and are less robust to occlusions. To address...

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Bibliographic Details
Main Authors: Zhongxiong Xu, Jiajun Hong, Yicong Yu, Chengzhu Lin, Linfei Yu, Meixian Xu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Graph convolutional network
self-attention
human pose embedding
probabilistic embedding
Online Access:https://ieeexplore.ieee.org/document/11119677/
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