… We build on research in recovering motion from video, in creating animations from motion …
The motion data were processed into a hierarchical skeleton (joint angles and pelvis position …

… learn spatial correlations in motion data. While most DNNs designed to address tasks related
to skeletal character animation … human skeleton, for example its symmetry or its hierarchical …

… synthesis is one of the key technologies in the field of computer animation and multimedia
… of data and so on. In fact, using deep learning techniques to construct human motions has …

… first time in a deep learning framework with neural networks to accomplish character animation
tasks such as motion prediction. Dual quaternions encode the hierarchical nature of a rig, …

… 3D human motion can be used to generate a variety of realistic new motions, thus is useful
for data-driven motion … of manual work and to automate the production of character animation. …

… in motion capture technology and deep learning methods … for character animation synthesis
is based on a deep recurrent … on a large database of motion capture data such that it can …

… animation synthesis and editing based on a deep learning framework, which can automatically
learn an embedding of motion data … a hierarchical RNN using a large motion dataset from …

… a novel deep learning framework for image animation. Given … , we propose using a deformation
module to align the features of … for each human body part in order to compute the feature …

… Rather, the brain is capable of learning muscle controls from … on machine learning, particularly
DNNs and deep learning. … motion skills using hierarchical deep reinforcement learning. …

… in computer animation, is the retargeting of motion from one … in human motion capture data
based on hierarchical aggregation. … A deep learning framework for character motion synthesis …