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Lightweight Cross-fusion Network on Human Pose Estimation for Edge Device
2021
IEEE Access
The deployment of human pose estimation on edge devices are essential task in computer vision. Due to memory and storage space limitations, it is difficult for edge devices to maintain implementing Convolutional Neural Networks, which deployed large-scale terminal platforms with abundant computing resources. This paper proposed novel Lightweight Cross-fusion Network on Human Pose Estimation with information sharing. Using state-of-the-art efficient neural architecture, and Ghost Net, as the
doi:10.1109/access.2021.3065574
fatcat:r2zl54crdnb5dgtzqdm6owoxzi