Diffusion models for eye-gaze trajectory generation using position and velocity representations

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arXiv:2609.05522v1 Announce Type: new Abstract: Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of privacy constraints. We address this using two complementary denoising diffusion probabilistic models (D…

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1. 2026-09-09 04:00 · arXiv cs.CV
   Diffusion models for eye-gaze trajectory generation using position and velocity representations