arXiv: cs.AI preprintsInternational6 November 2026
STAG-Net: Structure-Aware Attention over Landmark Groups for Lightweight Head Pose Estimation
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arXiv:2611.07828v1 Announce Type: cross Abstract: Head pose estimation is important for human computer interaction and driver monitoring, but many image based methods remain too costly for resource constrained deployment. We propose STAG-Net, a structure-aware attention over landmark groups for lightweight head Pose estimation that estimates head pose from facial landmarks using movement aware selection, spatial clustering, compact DeepSet encoders, self attention, and a global geometry descriptor. We develop variants using FaceMesh and Face Alignment Network landmarks and evaluate them under
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