Auto-Conditioned LSTM Network for Extended Complex Human Motion Synthesis (bibtex)
by Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, 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 LSTM Network for Extended Complex Human Motion Synthesis (Zimo Li, Yi Zhou, Shuangjiu Xiao, Chong He, Hao Li), In CoRR, volume abs/1707.05363, 2017.
Bibtex Entry:
@article{DBLP:journals/corr/LiZXHL17,
	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).},
	author = {Zimo Li and Yi Zhou and Shuangjiu Xiao and Chong He and Hao Li},
	title = {Auto-Conditioned {LSTM} Network for Extended Complex Human Motion Synthesis},
	journal = {CoRR},
	volume = {abs/1707.05363},
	year = {2017},
	url = {http://arxiv.org/abs/1707.05363},
	archivePrefix = {arXiv},
	eprint = {1707.05363},
	timestamp = {Mon, 13 Aug 2018 16:46:22 +0200},
	biburl = {https://dblp.org/rec/bib/journals/corr/LiZXHL17},
	bibsource = {dblp computer science bibliography, https://dblp.org}
}
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