Invention Grant
- Patent Title: Generating realistic animations for digital animation characters utilizing a generative adversarial network and a hip motion prediction network
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Application No.: US16451813Application Date: 2019-06-25
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Publication No.: US10964084B2Publication Date: 2021-03-30
- Inventor: Jingwan Lu , Yi Zhou , Connelly Barnes , Jimei Yang
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06T13/00
- IPC: G06T13/00 ; G06T13/80 ; G06F17/16 ; G06N3/04

Abstract:
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a digital animation of a digital animation character by utilizing a generative adversarial network and a hip motion prediction network. For example, the disclosed systems can utilize an unconditional generative adversarial network to generate a sequence of local poses of a digital animation character based on an input of a random code vector. The disclosed systems can also utilize a conditional generative adversarial network to generate a sequence of local poses based on an input of a set of keyframes. Based on the sequence of local poses, the disclosed systems can utilize a hip motion prediction network to generate a sequence of global poses based on hip velocities. In addition, the disclosed systems can generate an animation of a digital animation character based on the sequence of global poses.
Information query