.png){kind=icon}
返回
Learning Virtual Chimeras by Dynamic Motion Reassembly
.png){kind=icon}
PRE
AI
DOI：10.1145/3550454.3555489.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The Chimera is a mythological hybrid creature composed of different animal parts. The chimera's movements are highly dependent on the spatial and temporal alignments of its composing parts. In this paper, we present a novel algorithm that creates and animates chimeras by dynamically reassembling source characters and their movements. Our algorithm exploits a two-network architecture: part assembler and dynamic controller. The part assembler is a supervised learning layer that searches for the spatial alignment among body parts, assuming that the temporal alignment is provided. The dynamic controller is a reinforcement learning layer that learns robust control policy for a wide variety of potential temporal alignments. These two layers are tightly intertwined and learned simultaneously. The chimera animation generated by our algorithm is energy efficient and expressive in terms of describing weight shifting, balancing, and full-body coordination. We demonstrate the versatility of our algorithm by generating the motor skills of a large variety of chimeras from limited source characters.
Keyword:
Physics-Based Simulation
Data-Driven Animation
Deep Reinforcement Learning
期刊
IF:
9.5
论文数:
4.7K
被引数:
3.6W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容