컴퓨터 그래픽스 학회인 SIGGRAPH Asia 2019에 Motion AI 팀의 Fast Terrain-Adaptive Motion Generation using Deep Neural Networks 연구가 소개되었습니다.
Abstract
We propose a fast motion adaptation framework using deep neural networks. Traditionally, motion adaptation is performed via iterative numerical optimization.We adopted deep neural networks and replaced the iterative process to the feed-forward inference which consists of simple matrix multiplications. For efficient mapping from contact constraints to character motion, the proposed system is composed of two types of networks: trajectory and pose generators. The networks are trained using augmented motion capture data and are fine-tuned using the inverse kinematics loss. In experiments, our system successfully generates multi-contact motions of a hundred of characters in real-time, and the result motions contain the naturalness existing in the motion capture data.
Authors
Moonwon Yu, Byungjun Kwon, Hanyoung Jang(NCSOFT), Jongmin Kim, Shinjin Kang
Proceeding
SIGGRAPH Asia ‘19 ACM SIGGRAPH 2019 Technical Brief