A causal convolutional neural network for multi-subject motion modeling and generation

Autor:	Shuaiying Hou, Congyi Wang, Wenlin Zhuang, Yu Chen, Yangang Wang, Hujun Bao, Jinxiang Chai, Weiwei Xu
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	deep learning optimization motion generation motion denoising motion control Electronic computers. Computer science QA75.5-76.95
Zdroj:	Computational Visual Media, Vol 10, Iss 1, Pp 45-59 (2023)
Druh dokumentu:	article
ISSN:	2096-0433 2096-0662
DOI:	10.1007/s41095-022-0307-3
Popis:	Abstract Inspired by the success of WaveNet in multi-subject speech synthesis, we propose a novel neural network based on causal convolutions for multi-subject motion modeling and generation. The network can capture the intrinsic characteristics of the motion of different subjects, such as the influence of skeleton scale variation on motion style. Moreover, after fine-tuning the network using a small motion dataset for a novel skeleton that is not included in the training dataset, it is able to synthesize high-quality motions with a personalized style for the novel skeleton. The experimental results demonstrate that our network can model the intrinsic characteristics of motions well and can be applied to various motion modeling and synthesis tasks.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/3bd893f996924e05af59539a2860b8f2 Zobrazit plný text záznamu Full text from SpringerLink View record in DOAJ