AI RESEARCH
EgoTraj: Real-World Egocentric Human Trajectory Dataset for Multimodal Prediction
arXiv CS.LG
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ArXi:2605.19004v1 Announce Type: cross Accurately forecasting human trajectories from an egocentric perspective plays a central role in applications such as humanoid robotics, wearable sensing systems, and assistive navigation. However, progress in this direction remains limited due to the scarcity of egocentric trajectory datasets collected in real-world environments. Addressing this need, we