RGB-D-based human motion recognition with deep learning: A survey

@article{Wang2017RGBDbasedHM,
  title={RGB-D-based human motion recognition with deep learning: A survey},
  author={Pichao Wang and Wanqing Li and Philip Ogunbona and Jun Wan and Sergio Escalera},
  journal={ArXiv},
  year={2017},
  volume={abs/1711.08362}
}
Abstract Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much attention. Along with the development in artificial intelligence, deep learning techniques have gained remarkable success in computer vision. In particular, convolutional neural networks (CNN) have achieved great success for image-based tasks, and recurrent neural networks (RNN) are renowned for sequence-based… CONTINUE READING
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References

Publications referenced by this paper.
SHOWING 1-10 OF 175 REFERENCES

Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks

  • 2017 IEEE International Conference on Computer Vision (ICCV)
  • 2017
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Generalized Rank Pooling for Activity Recognition

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Global Context-Aware Attention LSTM Networks for 3D Action Recognition

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 15 EXCERPTS
HIGHLY INFLUENTIAL

Learning and Refining of Privileged Information-Based RNNs for Action Recognition from Depth Sequences

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos

  • 2017 IEEE International Conference on Computer Vision (ICCV)
  • 2017
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

Unsupervised Learning of Long-Term Motion Dynamics for Videos

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

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