3D-based Deep Convolutional Neural Network for action recognition with depth sequences
By Zhi Liu, Chenyang Zhang, Yingli Tian. 2016
158 citations recorded by the source corpus.
Subfields: 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 Computer Vision and Pattern Recognition
- Pichao Wang
- Wanqing Li
- Philip O. Ogunbona
- Sergio Escalera
- Jun Wan
- Zhimin Gao
- Chang-Fu Tang
- Yonghong Hou
In Human-Computer Interaction
- Pichao Wang
- Philip O. Ogunbona
- Wanqing Li
- Sergio Escalera
- Jun Wan
- Zhimin Gao
- Chang-Fu Tang
- Yonghong Hou
Citations in the corpus
- RGB-D-based Human Motion Recognition with Deep Learning: A Survey (2017, background): “25% MSR-Action3D [85] Depth 3DCNN None 84.”
- Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates (2017, neutral): “Skeleton-based action recognition has been explored in different aspects in recent years [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57].”