Towards Embedding Dynamic Personas in Interactive Robots: Masquerading Animated Social Kinematics (MASK)

no code implementations • 15 Mar 2024 • Jeongeun Park, Taemoon Jeong, Hyeonseong Kim, Taehyun Byun, Seungyoon Shin, Keunjun Choi, Jaewoon Kwon, Taeyoon Lee, Matthew Pan, Sungjoon Choi

This paper presents the design and development of an innovative interactive robotic system to enhance audience engagement using character-like personas.

Learning Joint Representation of Human Motion and Language

no code implementations • 27 Oct 2022 • Jihoon Kim, Youngjae Yu, Seungyoun Shin, Taehyun Byun, Sungjoon Choi

In this work, we present MoLang (a Motion-Language connecting model) for learning joint representation of human motion and language, leveraging both unpaired and paired datasets of motion and language modalities.

Action Recognition Contrastive Learning +2

Conditional Motion In-betweening

1 code implementation • 9 Feb 2022 • Jihoon Kim, Taehyun Byun, Seungyoun Shin, Jungdam Won, Sungjoon Choi

Motion in-betweening (MIB) is a process of generating intermediate skeletal movement between the given start and target poses while preserving the naturalness of the motion, such as periodic footstep motion while walking.

Pose Prediction