A Lightweight Context-Aware Feature Transformer Network for Human Pose Estimation
We propose a Context-aware Feature Transformer Network (CaFTNet), a novel network for human pose estimation. To address the issue of limited modeling of global dependencies in convolutional neural networks, we design the Transformerneck to strengthen the expressive power of features. Transformerneck...
Main Authors: | Yanli Ma, Qingxuan Shi, Fan Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-02-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/13/4/716 |
Similar Items
-
Curve Set Feature-Based Robust and Fast Pose Estimation Algorithm
by: Mingyu Li, et al.
Published: (2017-08-01) -
Regression-Based Camera Pose Estimation through Multi-Level Local Features and Global Features
by: Meng Xu, et al.
Published: (2023-04-01) -
Robust Head Pose Estimation Using Extreme Gradient Boosting Machine on Stacked Autoencoders Neural Network
by: Minh Thanh Vo, et al.
Published: (2020-01-01) -
Human Pose Estimation Based on Lightweight Multi-Scale Coordinate Attention
by: Xin Li, et al.
Published: (2023-03-01) -
Multiscale feature fusion network for monocular complex hand pose estimation
by: Zhi Zhan, et al.
Published: (2023-12-01)