SEGAR: Selective Enhancement for Generative Augmented Reality
arXiv:2603.24541v1 Announce Type: cross
Abstract: Generative world models offer a compelling foundation for augmented-reality (AR) applications: by predicting future image sequences that incorporate deliberate visual edits, they enable temporally cohe…