Presentation / Installation
3. Content-Preserving Motion Stylization using Variational Autoencoder
DescriptionThis work proposes a novel motion style transfer network that transfers motion styles among different motion categories using the concept of the variational autoencoder.
The proposed network is effective in transferring style among various motion categories and is also able to create stylized motion that is unseen in the dataset.
The proposed network is effective in transferring style among various motion categories and is also able to create stylized motion that is unseen in the dataset.
Event Type
Poster
TimeWednesday, 9 August 20239am - 5:30pm PDT
LocationWest Lobby Entrance
ACM Digital Library
Poster PDF
Session Time & Location
Artificial Intelligence/Machine Learning
FC
FCS
E
EFC
EE
