SPGformer: Serial–Parallel Hybrid GCN-Transformer With Graph-Oriented Encoder for 2-D-to-3-D Human Pose Estimation-Reference-Cited by-同舟云学术

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SPGformer: Serial–Parallel Hybrid GCN-Transformer With Graph-Oriented Encoder for 2-D-to-3-D Human Pose Estimation

Published:2024 Issue: Volume:73 Page:1-15
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Fang Qin¹^ORCID,Xu Zihan²^ORCID,Hu Mengxian²^ORCID,Zeng Qinyang²^ORCID,Liu Chengju²^ORCID,Chen Qijun²^ORCID

Affiliation:

1. Department of Control Science and Engineering, Robotics and Artificial Intelligence Laboratory (RAIL), College of Electronic and Information Engineering, Tongji University, Shanghai, China

2. Robotics and Artificial Intelligence Laboratory (RAIL), College of Electronic and Information Engineering, Tongji University, Shanghai, China

Funder

National Natural Science Foundation of China

Shanghai Science and Technology Innovation Action Plan

Shanghai Municipal Science and Technology Major Project

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10478968.pdf?arnumber=10478968

Reference45 articles.

1. Deep Learning-based Human Pose Estimation: A Survey

2. 3D Human Pose Estimation with Spatial and Temporal Transformers

3. Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition

4. Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose

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