arXiv:2606.24255v1 Announce Type: cross Abstract: Although text-to-motion generation has achieved strong progress in synthesizing realistic single-person motions from language, extending it to text-driven 3D human-human interaction (HHI) remains non-trivial, as HHI requires modeling the underlying \textbf{social structure} that governs phase progression, actor roles, and inter-actor coordination. In this paper, we formulate HHI generation as a social structure modeling and grounding problem: the model must first infer how an interaction unfolds and how the two actors coordinate their roles, an
The rapid progress in single-person motion generation is naturally extending to more complex human-human interactions, driven by computational advancements and demand for more sophisticated AI behaviors.
This development is crucial for creating more realistic and socially intelligent AI, impacting fields from virtual reality to robotics and AI agents requiring complex interaction modeling.
AI's ability to model and generate multi-human interactions, considering social structures, marks a significant leap from isolated single-actor movements.
- · AI research labs
- · Robotics companies
- · Virtual reality developers
- · Gaming industry
- · Developers of less sophisticated single-actor animation tools
- · AI systems lacking social cognition layers
More naturalistic and believable interactions in games, simulations, and virtual environments.
Enhanced capabilities for AI agents to operate in human-centric environments, understanding and predicting social cues.
The development of AI systems capable of choreographing and managing complex social dynamics in hybrid human-AI teams.
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Read at arXiv cs.AI