We introduce a novel deep learning framework for data-driven motion retargeting between
skeletons, which may have different structure, yet corresponding to homeomorphic graphs …

A good motion retargeting cannot be reached without reasonable consideration of source-
target differences on both the skeleton and shape geometry levels. In this work, we propose …

While virtual humans are proven tools for training, education and research, they are far from
realizing their full potential. Advances are needed in individual capabilities, such as …

In this paper, a deep learning-based iterative solving method for unsupervised motion
retargeting is proposed. Unlike existing methods, we do not utilize generative-adversarial …

Human hands, the primary means of non-verbal communication, convey intricate semantics
in various scenarios. Due to the high sensitivity of individuals to hand motions, even minor …

Motion mapping between characters with different structures but corresponding to
homeomorphic graphs, meanwhile preserving motion semantics and perceiving shape …

For the past 15 years, in computer-supported collaborative learning applications,
conversational agents have been used to structure group interactions in online chat-based …

ABSTRACT Humanoid three‐dimensional (3D) models can be easily acquired through
various sources, including through online marketplaces. The use of such models within a …

In this study, we propose a novel motion re‐targeting framework that provides natural
motions of target robot character models similar to the given source motions of a different …

Motion retargeting is an active research area in computer graphics and animation, allowing
for the transfer of motion from one character to another, thereby creating diverse animated …