Improving Human Pose Estimation With Self-Attention Generative Adversarial Networks

Improving Human Pose Estimation With Self-Attention Generative Adversarial Networks

Human pose estimation in images is challenging and important for many computer vision applications. Large improvements in human pose estimation have been achieved with the development of convolutional neural networks. Even though, when encountered some difficult cases even the state-of-the-art model...

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Bibliographic Details
Main Authors: Xiangyang Wang, Zhongzheng Cao, Rui Wang, Zhi Liu, Xiaoqiang Zhu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Human pose estimation
convolutional neural networks
stacked hourglass networks
self-attention GAN
Online Access:https://ieeexplore.ieee.org/document/8808903/

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