FlowAvatar：面向消费级XR设备的稀疏自我中心输入实现实时全身化身
FlowAvatar: Real-Time Full-Body Avatars from Sparse Egocentric Inputs on Consumer XR Devices
AI总结：
FlowAvatar系统在消费级XR设备上通过稀疏自我中心输入实现实时全身个性化化身，其姿态模型在AMASS基准上精度与一致性优异，两项用户研究证实追踪完整性与个性化外观互补可提升具现化效果。
摘要：
过往化身具现化研究分别探究了追踪完整性（身体、手部、面部的感知与复现精度）和个性化外观，二者均需专用实验室设备。现有系统未在独立头显上统一身体姿态、面部、手部及个性化外观，因此这些因素在消费级硬件上的相互作用仍是开放问题。我们提出FlowAvatar系统，可在消费级XR设备（Meta Quest Pro）上，通过稀疏自我中心输入实现带全身姿态、手部关节、面部表情及眼球追踪的实时个性化相似化身。我们的姿态模型在AMASS基准上，相较于过往工作达到了有竞争力的空间精度和最优的时间一致性，通过架构与损失消融验证了综合空间和时间损失，且能实时运行。两项用户研究（N=12、N=10）提供了一致证据：追踪完整性与个性化外观起互补作用，追踪完整性广泛提升感知运动质量，仅二者结合可实现正向的总体具现化效果。
英文摘要：
Prior avatar embodiment research has studied tracking completeness (how faithfully the body, hands, and face are sensed and reproduced) and personalized appearance in isolation, each requiring specialized lab equipment. How these factors interact on consumer hardware remains an open question, because no existing system unifies body pose, face, hands, and personalized appearance on a standalone headset. We present FlowAvatar, a system enabling real-time personalized look-alike avatars with full-body pose, hand articulation, facial expression, and eye gaze tracking from sparse egocentric inputs on consumer XR devices (Meta Quest Pro). Our pose model achieves competitive spatial accuracy and state-of-the-art temporal consistency on the AMASS benchmark against prior works with comprehensive spatial and temporal losses validated through architecture and loss ablations, while running in real-time. Two user studies (N=12, N=10) provide converging evidence that tracking completeness and personalized appearance serve complementary roles: tracking completeness broadly improves perceived motion quality, while only their combination achieves positive total embodiment.
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