Unsupervised Representation Learning With Long-Term Dynamics for Skeleton Based Action Recognition

@inproceedings{Zheng2018UnsupervisedRL,
  title={Unsupervised Representation Learning With Long-Term Dynamics for Skeleton Based Action Recognition},
  author={Nenggan Zheng and Jun Wen and Risheng Liu and Liangqu Long and Jianhua Dai and Zhefeng Gong},
  booktitle={AAAI},
  year={2018}
}
In recent years, skeleton based action recognition is becoming an increasingly attractive alternative to existing videobased approaches, beneficial from its robust and comprehensive 3D information. In this paper, we explore an unsupervised representation learning approach for the first time to capture the long-term global motion dynamics in skeleton sequences. We design a conditional skeleton inpainting architecture for learning a fixed-dimensional representation, guided by additional… CONTINUE READING

Figures, Tables, and Topics from this paper.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…