Jul 2026
MuViSeg: Multi-View Segment Correspondences from Dense Geometry Priors
This work proposes three learned matching heads: a LightGlue-style attention head with DoubleSoftmax scoring on frozen MASt3R descriptors; a DPT-style multi-scale fusion module that exposes layered spatial detail from the VGGT foundation model before pooling; and a multi-view extension that performs joint self-attention over segments drawn from several views at once, recovering transitive correspondences that strictly pairwise matchers cannot reach.
Denis Fatykhoph, Timur Akhtyamov, Konstantin Pakulev et al.
· arXiv.org · 0 citations