A cross-modal transformer using heterogeneous scene graphs predicts VR user trajectories more accurately than gaze- and point-cloud-only baselines on the CREATTIVE3D dataset.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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DiVR: incorporating context from diverse VR scenes for human trajectory prediction
A cross-modal transformer using heterogeneous scene graphs predicts VR user trajectories more accurately than gaze- and point-cloud-only baselines on the CREATTIVE3D dataset.