Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis (bibtex)

by Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, Zeng Huang and Hao Li

Abstract:

We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN).

Reference:

Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis (Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, Zeng Huang and Hao Li), 2017.

Bibtex Entry:

@misc{li2017autoconditioned,
    title = {Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis},
    author = {Zimo Li and Yi Zhou and Shuangjiu Xiao and Chong He and Zeng Huang and Hao Li},
    year = {2017},
    eprint = {1707.05363},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
	abstract = {We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN).}
	
}