AI RESEARCH
MV-RoMa: From Pairwise Matching into Multi-View Track Reconstruction
arXiv CS.CV
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ArXi:2603.27542v1 Announce Type: new Establishing consistent correspondences across images is essential for 3D vision tasks such as structure-from-motion (SfM), yet most existing matchers operate in a pairwise manner, often producing fragmented and geometrically inconsistent tracks when their predictions are chained across views. We propose MV-RoMa, a multi-view dense matching model that jointly estimates dense correspondences from a source image to multiple co-visible targets.