Learning features combination for human action recognition from skeleton sequences

By Diogo Carbonera Luvizon, Hedi Tabia, David Picard. 2017

108 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. David Picard
2. Siyuan Bian
3. Lixin Yang
4. Zhicun Chen
5. Cewu Lu
6. Hedi Tabia
7. Diogo Carbonera Luvizon
8. Chao Xu

In Computer Vision and Pattern Recognition

1. Jiefeng Li
2. Cewu Lu
3. Hedi Tabia
4. Diogo Carbonera Luvizon
5. David Picard
6. Siyuan Bian
7. Lixin Yang
8. Zhicun Chen

In Human-Computer Interaction

1. Jiefeng Li
2. David Picard
3. Siyuan Bian
4. Cewu Lu
5. Hedi Tabia
6. Diogo Carbonera Luvizon

Citations in the corpus

• 2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning (2018, background): “Differently from video based action recognition, 3D action recognition is mostly based on skeleton data as the primary information [29, 40].”
• HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation (2020, background): “It has a wide rage of application scenarios [52, 31, 27, 28, 8].”