InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction

Understand

Text-conditioned human motion generation has experienced significant advancements with diffusion models trained on extensive motion capture data and corresponding textual annotations.

• However, extending such success to 3D dynamic human-object interaction (HOI) generation faces notable challenges, primarily due to the lack of large-scale interaction data and comprehensive descriptions that align with these interactions.
• This paper takes the initiative and showcases the potential of generating human-object interactions without direct training on text-interaction pair data.
• Our key insight in achieving this is that interaction semantics and dynamics can be decoupled.