X's Day: Personality-Driven Virtual Human Behavior Generation

Haoyang Li;Zan Wang;Wei Liang;Yizhuo Wang
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Abstract

Developing convincing and realistic virtual human behavior is essential for enhancing user experiences in virtual reality (VR) and augmented reality (AR) settings. This paper introduces a novel task focused on generating long-term behaviors for virtual agents, guided by specific personality traits and contextual elements within 3D environments. We present a comprehensive framework capable of autonomously producing daily activities autoregressively. By modeling the intricate connections between personality characteristics and observable activities, we establish a hierarchical structure of Needs, Task, and Activity levels. Integrating a Behavior Planner and a World State module allows for the dynamic sampling of behaviors using large language models (LLMs), ensuring that generated activities remain relevant and responsive to environmental changes. Extensive experiments validate the effectiveness and adaptability of our approach across diverse scenarios. This research makes a significant contribution to the field by establishing a new paradigm for personalized and context-aware interactions with virtual humans, ultimately enhancing user engagement in immersive applications. Our project website is at: https://behavior.agent-x.cn/.
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X's Day:人格驱动的虚拟人行为生成。
在虚拟现实(VR)和增强现实(AR)环境中,开发令人信服且逼真的虚拟人行为对于提升用户体验至关重要。本文介绍了一项新任务,重点是在特定个性特征和三维环境中的上下文元素指导下,为虚拟代理生成长期行为。我们提出了一个能够自动生成日常活动的综合框架。通过对个性特征和可观察活动之间错综复杂的联系进行建模,我们建立了一个由需求、任务和活动三个层次组成的分层结构。将行为规划器和世界状态模块整合在一起,可以使用大型语言模型(LLM)对行为进行动态采样,确保生成的活动与环境变化保持相关并做出响应。大量实验验证了我们的方法在不同场景下的有效性和适应性。这项研究通过建立与虚拟人进行个性化和情境感知交互的新范例,为该领域做出了重大贡献,最终提高了用户在沉浸式应用中的参与度。我们的项目网站是:https://behavior.agent-x.cn/。
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